BigQuery is a cloud-based data warehouse built for data scientists and data engineers. The platform is highly scalable, able to store massive amounts of data, and integrates easily with Google Suite products. It includes a SQL workbench and allows multiple users to query data. New users may find that BigQuery’s expensive price tag, extremely technical learning curve, and lack of integrations to pull in data are a barrier to entry.
Panoply is the easiest way to sync, store, and access all your business data. The platform combines a powerful data warehouse with code-free ETL, which results in quick and easy setup and minimal upkeep. Users can query data directly in Panoply or connect their preferred analytical notebook or BI tool.
Cloud-based collection and retention of data.
Pipelines that sync data between a source and a destination.
Automated structuring, cleaning, and standardization of raw data.
A tool that enables you to create SQL queries to analyze data.
How complicated the tool is to use.
How much and what types of support are provided.
Features that ensure data control and consistency.
Protocols that ensure data safety and adherence to industry standards; includes SOC 2, HIPAA, and GDPR.
Built-in integrations with top business intelligence tools.
Built-in integrations with top ETL tools.
Built-in integrations with cloud-based platforms that connect applications, systems, and technologies.
Ability to try the product prior to purchasing.
BigQuery integrates easily with Google Suite products such as Google Data Studio, but lacks native integrations to ingest data from other platforms. Users will need to rely on their technical savvy and third party tools to pull in data from non-Google sources.
Panoply provides built-in ETL integrations with dozens of data sources, including popular cloud APIs, databases, CRMs, advertising platforms, and file storage systems. Users can also pipe data in through partners like Stitch or Fivetran or pull in data via an S3 bucket. Once data is synced, users can query it via Panoply’s workbench or connect their favorite BI tool.
Pricing for BigQuery is scalable but convoluted and includes many inputs, including charges for both active storage and long-term storage, and on-demand queries and flat-rate Queries. New users may find it difficult to estimate what their costs will be.
Panoply offers both monthly and annual plans starting as low as $200 per month. Its pricing model is simple and transparent: users pay for the number of data sources they use and the amount of data they store. There are no extra fees for adding users or the number of queries run, so cost is more predictable than with pay-by-the-hour or pay-by-the-row models.