End-to-end cloud data warehouse & management service.

Integrations

Structured & semi-structured data sources + analytics tools.

Customers

Trusted by data teams big & small. #1 in satisfaction on G2 Crowd.

Blog

Insights on data management, infrastructure, & analysis.

Pricing

Simple & transparent. 21-day free trial, no credit card required.

Demo

Schedule a test drive.

Integrations / Databases / PostgreSQL

Move PostgreSQL Data into a Data Warehouse in Minutes

At Panoply, we make it easy to integrate your platform with PostgreSQL and its module heavy sister, Postgres Plus. PostgreSQL is a popular open source database, known for its object RDBMS and community support. Panoply allows PostgreSQL users the opportunity to:

Import and access their Postgres data in real time
Combine their data with other sources, including other databases
Query raw data instantly

As a cloud based platform, Panoply reduces the infrastructure necessary for a traditional PostgreSQL data warehouse where most Postgres data is stored, and automatically applies ETL and ELT with no added work by the user. With Panoply, your PostgreSQL data is automatically collected, sorted, and ready to be analyzed.

Try Panoply

Panoply makes it easy to analyze PostgreSQL data

CHOOSING US

Why Panoply?

Use-Case Optimization

Analyzes queries and data – identifying the best configuration for each use case, adjusting it over time, and building indexes, sortkeys, diskeys, data types, vacuuming, and partitioning.

Query Optimization

Identifies queries that do not follow best practices – such as those that include nested loops or implicit casting – and rewrites them to an equivalent query requiring a fraction of the runtime or resources.

Server Optimization

Optimizes server configurations over time based on query patterns and by learning which server setup works best. The platform switches server types seamlessly and measures the resulting performance.

Updates, Upserts, and Deletions

Supports standard SQL update and upset operations out of the box – without worrying about vacuuming or rebuilding- unlike many analytical databases.

Semi-Structured Data Parsing

Supports semi-structured text values like nested JSON, user-agent strings, some standard log formats, CSV, and serialized Ruby objects – parsing these objects and normalizing them into a relational database design.

Nested Structures

Handles nested structures automatically, flattening them into several tables with a one-to- many relationship. The result is a ready-to- use relational database design for all current and future datasets.

Columnar Storage

Provides seamless data storage and management in a multitiered, columnar storage based on Amazon Redshift, Elasticsearch, and Hadoop or SS3.

Data Tracking and Alerts

Simplifies how you keep track of vast amounts of data – by identifying patterns, providing notification of anomalies, and generating alerts when the results of arbitrary SQL queries exceed predefined thresholds.

Backup and Recovery

Automatically backs up changes to data to a redundant S3 storage, optionally saved in two different availability zones across continents – enabling full recovery to any point in time.