Best MongoDB Alternatives for 2027: Our Top 9

Based on our testing of 11 databases, PostgreSQL is the best MongoDB alternative for most teams because it combines indexed JSONB documents, SQL joins and ACID transactions, and a permissive license.

We’ll walk you through each database’s document model, managed pricing, licensing, and migration drawbacks so you can choose a replacement for the workload MongoDB no longer serves well. MongoDB itself uses SSPL, so a move motivated by licensing needs a different shortlist from a move motivated by search or global transactions.

Key Takeaways 🔍

• PostgreSQL is our top pick for JSONB flexibility, relational queries, and broad managed hosting choice
• Managed plans start around $5 per month; most picks offer free self-hosting, although CockroachDB and ArangoDB impose eligibility restrictions and DynamoDB is AWS-only
• PostgreSQL, MySQL Community, Cassandra, and CouchDB are open source; Redis and Elasticsearch offer AGPL options, while CockroachDB and ArangoDB remain source-available
• Redis and Elasticsearch work best beside a system of record, handling hot data and search rather than replacing your entire database
• Choose DynamoDB if you’re committed to AWS and want serverless operation, since on-demand billing removes the need to provision database servers

At Panoply, we evaluate database replacements across document model fit and migration path (30%), query and transaction power (20%), scalability and operations (15%), pricing and total cost (15%), license and openness (10%), and ecosystem and maintenance (10%).

Our migration evaluations start with collection modeling and the queries an application depends on, rather than feature counts alone. We prioritize replacements that preserve useful document flexibility without hiding query rewrites or operating costs.

MongoDB Alternatives Comparison Table

Shortlist MongoDB alternatives by workload and license before comparing their managed prices. These entry plans use different deployment sizes and billing models, so a cheaper starting price does not establish lower production costs for the same application:

Database	Best for	Data model	Open source license	Free option	Managed starting price	Recommended for
PostgreSQL	Best overall	Relational + JSONB	PostgreSQL License	Self-hosted; Neon and Supabase tiers	$5/month, cluster-based, PlanetScale Postgres, us-east-1	Most apps leaving MongoDB
MySQL	Existing SQL teams	Relational + JSON	GPLv2 Community	Self-hosted Community	$39/month, cluster-based, PlanetScale Vitess, us-east-1	Teams with MySQL skills
Amazon DynamoDB	Serverless	Key-value / document	No, proprietary	25 GB; 25 provisioned RCU/WCU	$0.625/million write request units, on-demand, us-east-1	AWS-native apps
Apache Cassandra	Write-heavy scale	Wide-column	Apache 2.0	Self-hosted; Astra free tier	Astra usage billing through IBM; request current regional rates	Multi-region events and time-series data
Apache CouchDB	Offline-first sync	JSON document	Apache 2.0	Self-hosted; Cloudant Lite	About $75/month, provisioned throughput; confirm IBM region	Mobile and edge sync
CockroachDB	Global transactions	Distributed SQL	No, source-available	Individuals; companies under $10M revenue, with telemetry	$0.092/vCPU-hour, Standard, AWS us-east-1	Multi-region ACID
Redis	Hot data and caching	In-memory multi-model	AGPLv3 option in Redis 8	Self-hosted; 30 MB cloud database	About $5/month, hourly Essentials billing; confirm region	Sessions, cache, hot documents
Elasticsearch	Search-heavy apps	Search engine with JSON documents	AGPLv3 source option	Self-hosted; cloud trial	Hosted from about $114/month, provisioned resources; confirm region	Catalog and log search
ArangoDB	Graph + documents	Multi-model	No, BSL 1.1	Community: 100 GiB, non-commercial or internal use	Quote-based managed service; request regional quote	Connected data

1. PostgreSQL: Best Overall MongoDB Alternative

• PostgreSQL pricing: Free to self-host; managed from $5 per month, with free tiers on Neon and Supabase
• Open source license: Yes, permissive PostgreSQL License
• Compare: Read our PostgreSQL vs MySQL comparison

PostgreSQL is our best overall MongoDB alternative because JSONB with GIN indexes preserves document flexibility while SQL joins handle relationships without duplicating everything. Keep variable attributes in documents and give frequently queried or updated fields their own columns.

However, PostgreSQL lacks built-in sharding, so horizontal write scaling needs more architecture than MongoDB’s native approach. Choose Cassandra for distributed write-heavy workloads or CockroachDB when distributed transactions drive the decision.

Pros

• ✔️ JSONB documents with GIN indexing
• ✔️ Full ACID transactions and SQL joins
• ✔️ Permissive PostgreSQL License
• ✔️ Broad managed hosting choice

Cons

• ❌ No built-in sharding for write scale-out
• ❌ Whole-value rewrites when updating JSONB
• ❌ MQL and aggregation pipelines requiring SQL rewrites

What’s new with PostgreSQL? ⬇️

PostgreSQL 18 introduced asynchronous I/O for supported read operations, alongside uuidv7() and virtual generated columns. PostgreSQL 19 has reached release-candidate status, but choose a supported production release rather than making a migration depend on prerelease software. Teams on older installations should also check the support window before moving more application data into them.

Why use PostgreSQL in 2026? ⬇️

PostgreSQL lets you consolidate document and relational workloads instead of maintaining a separate database for each application feature. Extensions also provide a route to vector functionality alongside operational data. We recommend it when leaving MongoDB should simplify your stack, especially if reporting already needs SQL joins across otherwise disconnected collections.

My PostgreSQL testing notes ⬇️

I start with a collection exported as JSON, load it into a jsonb column, and add a GIN index for @> containment queries. That preserves the document shape while making the query rewrite concrete. I then separate frequently updated fields from the document rather than treating the initial import as the finished schema.

Changing a key rewrites the JSONB value, and large values use TOAST storage, so an oversized document can make small updates unnecessarily expensive. I keep flexible attributes in JSONB and use regular columns where the application repeatedly changes individual values. Embedded arrays need the same deliberate choice, so make sure you decide whether each becomes a child table or stays in jsonb.

How Much Does PostgreSQL Cost?

PostgreSQL has no software license fee, but self-hosting still requires infrastructure and operations. Compare managed compute and storage together, not just the plan headline.

Option	Price	Billing basis	Free option
Self-hosted PostgreSQL	$0 software	Your own servers	Yes
Neon Launch	$0.106/CU-hour + $0.35/GB-month	Hourly usage, monthly invoice; confirm deployment region	Free plan: 100 CU-hours/project
Supabase Pro	From $25/month	Per organization plus hourly project compute; confirm region	500 MB; pauses after 1 inactive week
AWS RDS PostgreSQL, db.t4g.micro	About $12/month + $0.115/GB-month storage	Instance-hours and storage, us-east-1	New-account eligibility applies
PlanetScale Postgres	From $5/month single node; $15 HA	Cluster size plus storage, AWS us-east-1	No

2. MySQL: Best for Existing SQL Teams

• MySQL pricing: Free Community Edition; managed PlanetScale Vitess from $39 per month; commercial Enterprise subscriptions
• Open source license: Yes, GPLv2 Community Edition
• Compare: Read our guide to MongoDB and MySQL

MySQL is our pick for existing SQL teams because JSON columns and writable Duality Views let applications work with documents over relational data. Your developers can reuse familiar database skills instead of learning another engine.

That said, PostgreSQL offers richer JSON querying and indexing. Choose MySQL when consolidating onto an existing relational stack matters more than getting the strongest document-query tooling.

Pros

• ✔️ Native JSON type with functional indexes
• ✔️ Writable JSON Duality Views in Community Edition
• ✔️ Extensive hosting and tooling ecosystem
• ✔️ Familiar relational model for backend teams

Cons

• ❌ Less flexible JSON tooling than PostgreSQL JSONB
• ❌ Oracle ownership and separate commercial edition
• ❌ Calendar versioning alongside existing LTS tracks

What’s new with MySQL? ⬇️

MySQL 9.7 LTS brought writable JSON Duality Views and the hypergraph optimizer to Community Edition. The Innovation track now uses 26.x calendar versioning, while LTS releases retain their sequential numbering. The Thread Pool plugin also joined Community through the Innovation track, so check feature availability against your chosen release rather than the MySQL name alone.

Why use MySQL in 2026? ⬇️

MySQL makes sense when MongoDB is the odd database out in an otherwise relational stack. Duality Views support document-shaped reads and writes while the underlying data lives in normalized tables. That creates a gradual migration path, although you still need to replace MongoDB queries and driver calls rather than simply change a connection string.

My MySQL testing notes ⬇️

I map a frequently queried JSON path to a generated column or functional index before evaluating the query. For related data, I use a writable JSON Duality View to expose documents backed by linked tables. This separates the application’s document shape from the relational storage model instead of preserving every embedded object unchanged.

MySQL’s JSON operators do not provide the same containment-query workflow as PostgreSQL JSONB, so I compare the filters the application actually needs. I also treat package configuration as part of the migration, not an unrelated maintenance task. LTS and Innovation tracks have different feature sets, so make sure you pin the LTS track you want in your package configuration.

How Much Does MySQL Cost?

Community Edition is free software. PlanetScale Vitess provides managed MySQL compatibility, while Oracle sells Enterprise Edition through a commercial subscription.

Option	Price	Billing basis	Free option
MySQL Community Edition	$0 software	Self-hosted infrastructure	Yes
PlanetScale Vitess	From $39/month	Cluster size, storage, backups, and egress; us-east-1	No
MySQL Enterprise Edition	Request Oracle pricing	Annual commercial subscription	No

3. Amazon DynamoDB: Best Serverless Option

• DynamoDB pricing: On-demand requests or provisioned capacity; always-free storage allowance of 25 GB
• Open source license: No, proprietary AWS managed service
• Compare: Read our DynamoDB vs MongoDB comparison

DynamoDB is our best serverless MongoDB alternative because AWS handles servers and upgrades, while on-demand capacity removes manual throughput provisioning. Global tables also offer multi-region strong consistency for applications that need it.

However, key-based queries demand more upfront modeling than MongoDB’s flexible filters. Its 400 KB item cap is much smaller than MongoDB’s 16 MB document limit, and PostgreSQL is better for changing, ad hoc queries.

Pros

• ✔️ Serverless operation without database server maintenance
• ✔️ On-demand pay-per-request billing
• ✔️ Multi-region strongly consistent global tables
• ✔️ Always-free storage and provisioned capacity allowances

Cons

• ❌ Queries constrained by partition keys and indexes
• ❌ Maximum item size of 400 KB
• ❌ Complete dependence on AWS

What’s new with DynamoDB? ⬇️

Multi-region strong consistency is generally available for global tables, with AWS describing the design as providing zero recovery-point loss. AWS Fault Injection Service also supports these tables, giving you a way to exercise failure scenarios instead of assuming that regional replication alone proves resilience.

Why use DynamoDB in 2026? ⬇️

DynamoDB suits small AWS teams whose traffic varies too much for an always-on cluster to feel economical. On-demand billing follows request usage, although scans and replication can still raise the bill. Choose the global-table consistency mode before creating the table because you cannot change it afterward.

My DynamoDB testing notes ⬇️

I list application access patterns before choosing a partition key and sort key, then add a global secondary index for another lookup path. Unlike a MongoDB collection, the DynamoDB table design needs to reflect those queries from the beginning. An access pattern outside that design can require a Scan, consuming reads across the table rather than only matching items.

I also check embedded document size before preserving a MongoDB collection’s structure, because oversized documents need splitting into smaller items. That changes how the application assembles related data and makes a direct collection copy insufficient. If you cannot list your queries upfront, start with PostgreSQL instead.

How Much Does DynamoDB Cost?

Backups, global-table replication, and data transfer bill separately. The free provisioned-capacity allowance does not make equivalent on-demand requests free.

Option	Price	Billing basis	Free option
On-demand writes	$0.625/million write request units	Request units, us-east-1	Free capacity allowance applies to provisioned mode
On-demand reads	$0.125/million read request units	Request units, us-east-1	Same restriction
Provisioned capacity	$0.00065/WCU-hour; $0.00013/RCU-hour	Capacity-unit hours, us-east-1	25 WCU and 25 RCU
Standard storage	$0.25/GB-month	Stored GB-month, us-east-1	25 GB

4. Apache Cassandra: Best for Write-Heavy Scale

• Cassandra pricing: Free to self-host; managed Astra DB uses pay-as-you-go billing through IBM
• Open source license: Yes, Apache 2.0
• Compare: Read our Cassandra vs MongoDB comparison

Cassandra is our write-heavy choice because its masterless architecture distributes writes across nodes and datacenters without relying on a single primary. Storage-Attached Indexes broaden the queries you can support beyond basic partition lookups.

However, CQL lacks joins and MongoDB-style aggregation pipelines. Choose CockroachDB when your application needs production-ready transactions spanning partitions rather than primarily distributed write throughput.

Pros

• ✔️ Write scale-out and multi-datacenter replication
• ✔️ Storage-Attached Indexes and native vector search
• ✔️ Apache 2.0 license
• ✔️ Masterless architecture without a single primary

Cons

• ❌ Query-first modeling and denormalized data copies
• ❌ No joins and limited aggregation
• ❌ Multi-partition ACID transactions still in alpha

What’s new with Cassandra? ⬇️

Cassandra 5.0 added Storage-Attached Indexes and native vector search, alongside improvements to compaction and storage structures. Accord introduces multi-partition transactions in the next major branch, but remains alpha rather than a production migration foundation. IBM also completed its DataStax acquisition, bringing Astra DB into its watsonx.data offering.

Why use Cassandra in 2026? ⬇️

Cassandra fits event and time-series workloads that need writes distributed across regions under a permissive license. Native vector functionality can keep embeddings beside operational data without changing database families. Choose it for predictable access patterns and distributed writes, not as a general MongoDB alternative for applications that frequently invent new filters.

My Cassandra testing notes ⬇️

I design Cassandra tables around queries, accepting denormalized copies when different access patterns need different keys. I choose partition keys that avoid concentrating writes on a small set of partitions. CQL looks familiar to SQL users, but unsupported filters can require ALLOW FILTERING, which does not replace a sound access path.

Storage-Attached Indexes provide another route for suitable filters, but they do not supply MongoDB aggregation pipelines or relational joins. I move that logic into application code or separate analytics tooling instead of expecting CQL syntax to translate it. Like DynamoDB, Cassandra rewards key-first design, but it runs outside AWS, so make sure you weigh hosting freedom against cluster operations.

How Much Does Cassandra Cost?

IBM sells Astra DB through watsonx.data but does not publish current request-unit rates. Request current rates from IBM, including storage and transfer for your deployment region.

Option	Price	Billing basis	Free option
Apache Cassandra	$0 software	Your own servers	Yes
DataStax Astra DB, IBM	Request current rates from IBM	Request units, storage, and transfer; request deployment-region quote	Free tier available

5. Apache CouchDB: Best for Offline-First Sync

• CouchDB pricing: Free to self-host; Cloudant Lite is free, with Standard starting around $75 per month
• Open source license: Yes, Apache 2.0
• Latest release: CouchDB 3.5.3

CouchDB is our offline-first pick because its JSON documents and multi-master replication let devices and servers exchange changes when connectivity returns. Its HTTP API also keeps basic document operations accessible without a specialized query driver.

However, CouchDB has fewer managed hosts and less query flexibility than PostgreSQL. Choose it for replication behavior, not because JSON storage makes it a drop-in MongoDB replacement.

Pros

• ✔️ Native JSON documents over HTTP
• ✔️ Multi-master replication for offline-first applications
• ✔️ Apache 2.0 license
• ✔️ Lucene-based Nouveau full-text search

Cons

• ❌ Smaller ecosystem and managed hosting selection
• ❌ No joins and limited complex-query flexibility
• ❌ Application-owned revision conflict resolution

What’s new with CouchDB? ⬇️

CouchDB’s current release line adds Nouveau search on Lucene, giving the document store a newer full-text indexing option. Maintenance updates include bulk index updates and automatic cleanup of Nouveau and Clouseau indexes. Self-hosters also need Erlang/OTP 26 or later, so include the runtime requirement in an existing installation’s upgrade plan.

Why use CouchDB in 2026? ⬇️

CouchDB remains distinctive for field and edge applications that cannot assume continuous connectivity. Its replication protocol is a stronger reason to choose it than generic promises about flexible schemas. If your application needs ordinary online CRUD and relational reporting instead, PostgreSQL is usually the more versatile destination.

My CouchDB testing notes ⬇️

I start with HTTP document operations using curl, then follow revision behavior before adding synchronization between databases. An update must carry the current _rev; a stale revision produces a conflict rather than silently replacing the document. I also add suitable indexes for Mango queries instead of relying on database scans.

Continuous replication moves changes between databases, but the application still owns conflict resolution when copies diverge. I treat MongoDB aggregation logic as a separate migration task because rebuilding it as CouchDB views changes the query implementation. Choose CouchDB for offline synchronization; skip it if complex joins and reporting are the main reasons you are moving.

How Much Does CouchDB Cost?

Cloudant is IBM’s managed, CouchDB-compatible service, not a requirement for running Apache CouchDB. Confirm regional throughput pricing before choosing a paid configuration.

Option	Price	Billing basis	Free option
Apache CouchDB	$0 software	Your own servers	Yes
IBM Cloudant Lite	$0	20 reads/second, 10 writes/second, 1 GB; IBM region selected at signup	Yes
IBM Cloudant Standard	About $75/month; $1/additional GB-month	Provisioned throughput; base includes 100 reads/second, 50 writes/second, 20 GB; confirm IBM region	Eligible new users: $250 credit

6. CockroachDB: Best for Global Transactions

• CockroachDB pricing: Free Enterprise eligibility for individuals and companies under $10M annual revenue; Cloud Standard from $0.092 per vCPU-hour
• Open source license: No, source-available CockroachDB Software License
• Latest release: v26.2 release line

CockroachDB is our global-transactions pick because it combines serializable SQL transactions with automatic sharding and regional data placement. PostgreSQL wire compatibility lets you reuse familiar drivers, although compatibility does not make the databases identical.

That said, Core’s retirement ended unrestricted free self-hosting under that edition. PostgreSQL is the cheaper, simpler choice when your application does not need distributed transactions across regions.

Pros

• ✔️ Multi-region ACID transactions
• ✔️ Automatic sharding and rebalancing
• ✔️ PostgreSQL wire compatibility and JSONB
• ✔️ Vector indexes for retrieval features

Cons

• ❌ Proprietary license after Core’s retirement
• ❌ Revenue-limited free company licensing with telemetry
• ❌ Higher managed entry cost than single-node PostgreSQL

What’s new with CockroachDB? ⬇️

The current release line adds fuzzy string-matching functions and post-quantum TLS support. Vector indexes are also available, with the relevant feature setting required before use. Cloud plans now use Standard and Mission Critical names, and new organizations receive a time-limited credit trial rather than a permanent free plan.

Why use CockroachDB in 2026? ⬇️

CockroachDB suits applications that need regional data placement without maintaining separate transactional databases for each geography. Its distributed SQL architecture handles sharding below the application layer. We recommend paying for that capability when global consistency or residency requirements justify the additional licensing and operating complexity.

My CockroachDB testing notes ⬇️

I connect with a PostgreSQL driver, then use an inverted index for JSONB queries rather than assuming every PostgreSQL indexing behavior carries over. Serializable transactions can return retryable errors under contention, so I include application retry logic in the migration plan. Vector indexing also requires enabling feature.vector_index.enabled before creating the index.

For self-hosting, I include the Enterprise license and telemetry requirements in deployment planning, even when the organization qualifies for free use. Those requirements remain separate from whether the application’s SQL works. If your users and transactional requirements sit in one region, start with PostgreSQL before paying for distributed capabilities.

How Much Does CockroachDB Cost?

Core retired in November 2024. Free Enterprise eligibility requires annual renewal and telemetry; companies outside the revenue threshold need a commercial agreement.

Option	Price	Billing basis	Free option
Self-hosted Enterprise, eligible users	$0 for individuals and companies under $10M annual revenue	Annual license renewal; telemetry required	Yes
Cloud Standard	$0.092/vCPU-hour; example around $203/month for 2 vCPU and 100 GB	Provisioned compute, AWS us-east-1; storage, backup, and transfer separately metered	30-day trial, $400 credit
Cloud Mission Critical	$0.162/vCPU-hour	Provisioned compute, AWS us-east-1; additional resource charges	Same trial
Self-hosted Enterprise, larger companies	Request quote	Annual commercial license	No

7. Redis: Best for Hot Data and Caching

• Redis pricing: Free Redis Open Source; Cloud Essentials around $5 per month; free 30 MB cloud database
• Open source license: Redis 8 offers AGPLv3 alongside RSALv2 and SSPLv1
• Compare: Read our Redis vs MongoDB comparison

Redis works best beside PostgreSQL or another primary database, not as a wholesale replacement for a large MongoDB deployment. It wins for hot data because in-memory storage comes with integrated JSON commands and a query engine.

However, RAM costs constrain dataset size much sooner than disk-based storage. Choose PostgreSQL for large document collections that do not need an in-memory access layer.

Pros

• ✔️ In-memory access for hot data
• ✔️ Integrated JSON, query engine, and time series
• ✔️ AGPLv3 open source option
• ✔️ Inexpensive managed entry plan

Cons

• ❌ Memory-based dataset sizing and cost
• ❌ Poor fit for large primary document collections
• ❌ Source-available-only licensing in Redis 7.4 to 7.8, with no open source option

What’s new with Redis? ⬇️

Redis 8 combined Redis Stack capabilities with Redis Open Source, including JSON and the query engine without separate module installation. The stable release line is now 8.10.x, while vector sets entered the unified product as a beta feature. Check feature maturity before making vector sets a production dependency.

Why use Redis in 2026? ⬇️

Redis suits features that repeatedly access a small, fast-changing working set, such as session state and rate limits. The AGPL option restores an open source route, but Redis 7.4 to 7.8 offer only RSALv2 or SSPLv1. Earlier releases through 7.2 use BSD licensing, so identify the version before applying assumptions from an older deployment.

My Redis testing notes ⬇️

I use JSON.SET and JSON.GET for documents, then create a JSON index with FT.CREATE for searchable fields. TTLs let cached copies expire while authoritative records remain elsewhere. I configure memory limits and RDB or AOF persistence alongside those commands rather than treating persistence as an afterthought.

When the working set outgrows available memory, the deployment needs eviction or a larger allocation rather than an unlimited document store. I separate cached documents from authoritative data before making that trade-off. Redis is strongest as a hot-data layer, so make sure you keep your system of record in PostgreSQL or another suitable pick.

How Much Does Redis Cost?

Redis Cloud’s entry price covers a small allocation. Pro’s monthly minimum matters more than its headline hourly rate.

Option	Price	Billing basis	Free option
Redis Open Source	$0 software	Self-hosted infrastructure	Yes
Redis Cloud Free	$0	30 MB database; select available region	Yes
Redis Cloud Essentials	From $0.007/hour, about $5/month	Hourly; 250 MB to 100 GB; confirm cloud and region	No
Redis Cloud Pro	From $0.014/hour; $200/month minimum	Hourly or annual; dedicated deployments; confirm region	No

8. Elasticsearch: Best for Search-Heavy Apps

• Elasticsearch pricing: Free self-managed source option; Elastic Cloud Hosted from about $114 per month
• Open source license: AGPLv3 source option alongside SSPLv1 and Elastic License 2.0
• Review: Read our Elasticsearch review

Elasticsearch is a search companion: keep authoritative records in PostgreSQL or another primary database and synchronize searchable documents into it. It wins for search-heavy applications because relevance ranking and vector retrieval go beyond basic document filtering.

However, Elasticsearch adds operational work around mappings, shards, and memory. Start with PostgreSQL when simple full-text search is enough and another cluster would add unnecessary complexity.

Pros

• ✔️ Full-text and vector search
• ✔️ ES|QL LOOKUP JOIN for enrichment
• ✔️ AGPLv3 source option
• ✔️ Search aggregations for analytics

Cons

• ❌ Unsuitable default for a transactional system of record
• ❌ Shard, mapping, and heap management
• ❌ Multiple licenses requiring deployment-specific review

What’s new with Elasticsearch? ⬇️

Elasticsearch’s current stable branch is 9.5.x, and ES|QL LOOKUP JOIN and cross-cluster search are generally available. Elastic also offers AGPLv3 alongside its existing source-code licensing choices. New feature development focuses on the current major release line, so older deployments should not assume feature parity.

Why use Elasticsearch in 2026? ⬇️

Elasticsearch deserves a place in applications that combine keyword relevance with vector retrieval. Product catalogs also benefit from aggregations alongside ranked search results. Choose it when search quality is a core application requirement, not because accepting JSON documents makes Elasticsearch equivalent to a transactional document database.

My Elasticsearch testing notes ⬇️

I define explicit mappings for important fields instead of letting dynamic mapping determine their types from the first incoming documents. I use ES|QL LOOKUP JOIN for enrichment, not as a substitute for transactional joins in the primary database. Search is near real time, so newly indexed documents may not appear until a refresh.

I keep authoritative writes in the primary database and synchronize the search index separately, accepting that search visibility follows its own update cycle. That separation makes Elasticsearch’s role explicit instead of asking it to satisfy every database requirement. Skip Elasticsearch if you only need simple filters; PostgreSQL full-text search may be enough.

How Much Does Elasticsearch Cost?

The serverless example below is an observability logs tier, not general search pricing. Budget search deployments using their actual resource configuration.

Option	Price	Billing basis	Free option
Self-managed Elasticsearch	$0 under AGPL source option	Your own servers; paid tiers use node and RAM pricing	Yes
Elastic Cloud Hosted	From about $114/month	Provisioned resources, pay-as-you-go or prepaid; confirm cloud and region	Free trial
Serverless Observability Logs Essentials	From $0.07/GB ingested + $0.017/GB-month retained	Ingestion and retention; confirm deployment region	Free trial

9. ArangoDB: Best for Graph Plus Documents

• ArangoDB pricing: Free Community binaries with a 100 GiB cap and non-commercial or internal-use restrictions; paid plans by quote
• Open source license: No, BSL 1.1
• Latest release: ArangoDB 3.12.13

ArangoDB wins for connected documents because AQL combines document filtering with graph traversal and joins across collections. That suits relationship-heavy data that becomes awkward to express through repeated MongoDB lookups.

However, its source license and Community binary restrictions weaken the case for leaving MongoDB over SSPL. Choose PostgreSQL or CouchDB when licensing freedom matters more than graph features.

Pros

• ✔️ Documents, graphs, search, and vectors together
• ✔️ AQL joins and graph traversals
• ✔️ Enterprise features in current Community binaries

Cons

• ❌ Source-available BSL rather than open source
• ❌ Community dataset cap and use restrictions
• ❌ Quote-only managed pricing

What’s new with ArangoDB? ⬇️

ArangoDB’s current branch moved from Apache licensing to BSL, with conversion to Apache after the specified waiting period. Community binaries gained Enterprise features but retain separate usage restrictions. Native Windows and macOS server builds also gave way to containers, while JavaScript transactions are deprecated.

Why use ArangoDB in 2026? ⬇️

ArangoDB suits connected-data applications that need graph traversal alongside document and vector retrieval. Multi-hop graph traversal across related documents is a stronger reason to choose ArangoDB than ordinary JSON CRUD. If relationships are shallow, PostgreSQL’s relational joins may solve the problem without introducing ArangoDB’s licensing constraints.

My ArangoDB testing notes ⬇️

I use a container for local evaluation and write an AQL query that filters documents, follows edges, and returns related records. I check the Community terms and dataset cap before expanding that prototype into a deployment. I also avoid building new migration logic around deprecated JavaScript transactions.

AQL’s combined graph and document model earns consideration when traversing relationships is central to the application. The Community restrictions still apply even when its included features meet the technical requirements. If your graph needs are light, test PostgreSQL recursive queries before adopting another database.

How Much Does ArangoDB Cost?

Arango does not publish managed prices. Request a quote covering your deployment region and intended commercial use.

Option	Price	Billing basis	Free option
Community Edition	$0	Self-hosted; 100 GiB cap; non-commercial or internal use	Yes
Enterprise, self-managed	Quote	Commercial license	No
Arango Managed Platform	Quote	Managed service; region specified in quote	Request pricing

How Do I Choose the Right MongoDB Alternative?

Choose a MongoDB alternative around the requirement MongoDB is failing, not the database with the longest feature list. PostgreSQL is our default for joins and permissive licensing; MySQL fits existing SQL teams, while DynamoDB suits AWS key-based access.

Cassandra handles distributed write-heavy workloads, and CockroachDB targets global transactions. Prioritize CouchDB for offline synchronization, or add Elasticsearch or Redis when search or hot-data access is the actual problem. MongoDB still handles deeply nested, write-heavy documents well, so staying is a valid decision.

• Can you list your top three query patterns, and can the target serve them without full scans?
• Do you need multi-document transactions or joins?
• Is the license open source, or source-available with usage restrictions?
• Do you want self-hosting or a managed service, and in which region?
• How large are your biggest documents?
• Does your team already know SQL?

Can I Switch From MongoDB Without Downtime?

Yes, but zero downtime is a migration outcome to engineer, not a database feature to assume. MQL-to-SQL rewrites often require more work than copying documents, and substantial migrations can take months.

Use change-data capture or suitable MongoDB ETL tools for copying and synchronization. Keep both databases aligned while validating the target; a successful initial load does not prove that cutover is safe.

1. Inventory dependencies and produce a list of collections, indexes, aggregation pipelines, and transactions to migrate.
2. Model your main queries on the target and confirm their access paths before loading everything.
3. Run both databases in parallel until representative query results agree.
4. Move reads first while maintaining synchronization and checking application behavior.
5. Cut over writes only after testing the rollback plan.
6. Validate counts and results after the load and cutover before retiring the original deployment.

How We Test and Rank MongoDB Alternatives

A native document model does not automatically make a database the best MongoDB alternative. Our evaluation starts with the original 11 candidates and retains nine based on migration suitability, maintenance, and licensing as well as database capabilities.

We work through collection modeling and application access patterns, giving document fit the largest weighting because preserving JSON alone does not preserve query behavior.

• Document model fit and migration path (30%): We assess document mapping, JSON support, key design, and the query rewrites required.
• Query and transaction power (20%): We evaluate joins, aggregations, secondary indexes, and multi-document ACID capabilities.
• Scalability and operations (15%): We assess sharding, multi-region replication, and the operational responsibilities retained by your team.
• Pricing and total cost (15%): We compare software costs with managed plans, billing units, and regional deployment requirements.
• License and openness (10%): We distinguish open source licenses from source-available licenses with commercial restrictions or usage caps.
• Ecosystem and maintenance (10%): We consider release activity, ownership, driver support, and managed hosting choice.

Prices current as of October 2026.

We rank PostgreSQL first because it combines document flexibility with relational capabilities and permissive licensing. MySQL follows for teams with existing expertise, while DynamoDB removes server management for AWS-native applications.

We favor Cassandra, CouchDB, and CockroachDB when their specialist capabilities match the workload. Redis and Elasticsearch rank lower because they primarily complement a system of record, not because their specialist capabilities are weak. ArangoDB combines graph and document queries, but its license restrictions and quote-only managed pricing limit its appeal as a general replacement.

Final Verdict: Which MongoDB Alternative Do I Recommend?

PostgreSQL is our best MongoDB alternative for most applications because JSONB preserves document flexibility while SQL adds joins and transactional modeling options. Its permissive license and broad hosting choice also leave you with fewer restrictions when deployment requirements change.

Choose DynamoDB for AWS serverless applications, Cassandra for write-heavy multi-region workloads, or CouchDB for offline synchronization. Start with a free tier or self-hosted instance and model your top three queries against representative documents before committing. Include an update operation as well as reads, since an easy initial import does not prove that the new data model fits your application.

FAQs

Is PostgreSQL really a good replacement for MongoDB?

Yes, PostgreSQL is a good MongoDB replacement for applications that need indexed JSON documents alongside SQL joins and ACID transactions. JSONB with GIN indexes supports flexible document queries without requiring every attribute to become a column.

However, migration still requires query rewrites, and updating JSONB rewrites the whole value. PostgreSQL also lacks built-in sharding. If write scale-out is your priority, consider Cassandra or CockroachDB rather than assuming PostgreSQL is universally better.

What is the best free, open source MongoDB alternative?

PostgreSQL is our best free MongoDB alternative because its permissive license accompanies strong JSONB and relational capabilities. Other open source options include:

• MySQL Community under GPLv2
• Cassandra and CouchDB under Apache 2.0
• Redis 8 and Elasticsearch with AGPLv3 options

Free software does not eliminate hosting costs. ArangoDB and CockroachDB are source-available, not open source; CockroachDB’s free Enterprise license also has company revenue eligibility limits and telemetry requirements.

Is there a MongoDB-compatible database so I don’t have to rewrite my queries?

Yes, FerretDB provides a MongoDB-compatible route on PostgreSQL, but compatibility is incomplete. FerretDB 2.0 uses Microsoft’s DocumentDB PostgreSQL extension, and DocumentDB is now a Linux Foundation project. FerretDB itself uses Apache 2.0 licensing.

This can reduce migration work compared with rewriting everything directly into SQL, but it does not guarantee that your application runs unchanged. Treat it as a compatibility bridge and test your drivers and aggregation pipelines before committing.

Why aren’t RethinkDB and OrientDB on this list anymore?

We dropped both because their maintenance and support positions make them poor targets for a new migration. RethinkDB’s last release was in December 2023, with only small maintenance changes afterward.

OrientDB still receives patches, but SAP ended commercial support and Sonatype retired it from Nexus. Both appeared in our original list, but ongoing patches alone do not replace a healthy support ecosystem.