Compare the Top OLAP Databases that integrate with PostgreSQL as of August 2025

This a list of OLAP Databases that integrate with PostgreSQL. Use the filters on the left to add additional filters for products that have integrations with PostgreSQL. View the products that work with PostgreSQL in the table below.

What are OLAP Databases for PostgreSQL?

OLAP (Online Analytical Processing) databases are designed to support complex queries and data analysis, typically for business intelligence and decision-making purposes. They enable users to interactively explore large volumes of multidimensional data, offering fast retrieval of insights across various dimensions such as time, geography, and product categories. OLAP databases use specialized structures like cubes to allow for rapid aggregation and calculation of data. These databases are highly optimized for read-heavy operations, making them ideal for generating reports, dashboards, and analytical queries. Overall, OLAP databases help organizations quickly analyze data to uncover patterns, trends, and insights for better decision-making. Compare and read user reviews of the best OLAP Databases for PostgreSQL currently available using the table below. This list is updated regularly.

  • 1
    icCube

    icCube

    icCube

    icCube is a drop-in replacement solution for SQL Server Analysis Services: - Logically compatible OLAP model and we help you with the migration - Continue using Excel and other XMLA / MDX clients - Deployment liberty (available as a docker) - On-the-fly dynamic MDX security, up to cell-level detail - Modern OLAP features: - 100+ new MDX functions - Categories - Subcubes - Native Java integration Patented MDX debugger And more The cherry on top: icCube comes with a web-based embeddable BI solution.
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    Starting Price: $20,000/year
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  • 2
    Oxla

    Oxla

    Oxla

    Purpose-built for compute, memory, and storage efficiency, Oxla is a self-hosted data warehouse optimized for large-scale, low-latency analytics with robust time-series support. Cloud data warehouses aren’t for everyone. At scale, long-term cloud compute costs outweigh short-term infrastructure savings, and regulated industries require full control over data beyond VPC and BYOC deployments. Oxla outperforms both legacy and cloud warehouses through efficiency, enabling scale for growing datasets with predictable costs, on-prem or in any cloud. Easily deploy, run, and maintain Oxla with Docker and YAML to power diverse workloads in a single, self-hosted data warehouse.
    Starting Price: $50 per CPU core / monthly
  • 3
    Apache Doris

    Apache Doris

    The Apache Software Foundation

    Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.
    Starting Price: Free
  • 4
    StarRocks

    StarRocks

    StarRocks

    Whether you're working with a single table or multiple, you'll experience at least 300% better performance on StarRocks compared to other popular solutions. From streaming data to data capture, with a rich set of connectors, you can ingest data into StarRocks in real time for the freshest insights. A query engine that adapts to your use cases. Without moving your data or rewriting SQL, StarRocks provides the flexibility to scale your analytics on demand with ease. StarRocks enables a rapid journey from data to insight. StarRocks' performance is unmatched and provides a unified OLAP solution covering the most popular data analytics scenarios. Whether you're working with a single table or multiple, you'll experience at least 300% better performance on StarRocks compared to other popular solutions. StarRocks' built-in memory-and-disk-based caching framework is specifically designed to minimize the I/O overhead of fetching data from external storage to accelerate query performance.
    Starting Price: Free
  • 5
    Hydra

    Hydra

    Hydra

    Hydra is an open source, column-oriented Postgres. Query billions of rows instantly, no code changes. Hydra parallelizes and vectorizes aggregates (COUNT, SUM, AVG) to deliver the speed you’ve always wanted on Postgres. Boost performance at every size! Set up Hydra in 5 minutes without changing your syntax, tools, data model, or extensions. Use Hydra Cloud for fully managed operations and smooth sailing. Different industries have different needs. Get better analytics with powerful Postgres extensions, custom functions, and take control. Built by you, for you. Hydra is the fastest Postgres in the market for analytics. Boost performance with columnar storage, vectorization, and query parallelization.
  • 6
    Citus

    Citus

    Citus Data

    Citus gives you the Postgres you love, plus the superpower of distributed tables. 100% open source. Now with schema-based and row-based sharding, plus Postgres 16 support. Scale Postgres by distributing data & queries. You can start with a single Citus node, then add nodes & rebalance shards when you need to grow. Speed up queries by 20x to 300x (or more) through parallelism, keeping more data in memory, higher I/O bandwidth, and columnar compression. Citus is an extension (not a fork) to the latest Postgres versions, so you can use your familiar SQL toolset & leverage your Postgres expertise. Reduce your infrastructure headaches by using a single database for both your transactional and analytical workloads. Download and use Citus open source for free. You can manage Citus yourself, embrace open source, and help us improve Citus via GitHub. Focus on your application & forget about your database. Run your app on Citus in the cloud with Azure Cosmos DB for PostgreSQL.
    Starting Price: $0.27 per hour
  • 7
    QuestDB

    QuestDB

    QuestDB

    QuestDB is a relational column-oriented database designed for time series and event data. It uses SQL with extensions for time series to assist with real-time analytics. These pages cover core concepts of QuestDB, including setup steps, usage guides, and reference documentation for syntax, APIs and configuration. This section describes the architecture of QuestDB, how it stores and queries data, and introduces features and capabilities unique to the system. Designated timestamp is a core feature that enables time-oriented language capabilities and partitioning. Symbol type makes storing and retrieving repetitive strings efficient. Storage model describes how QuestDB stores records and partitions within tables. Indexes can be used for faster read access on specific columns. Partitions can be used for significant performance benefits on calculations and queries. SQL extensions allow performant time series analysis with a concise syntax.
  • 8
    AlloyDB

    AlloyDB

    Google

    A fully managed PostgreSQL-compatible database service for your most demanding enterprise workloads. AlloyDB combines the best of Google with PostgreSQL, for superior performance, scale, and availability. Fully compatible with PostgreSQL, providing flexibility and true portability for your workloads. Superior performance, 4x faster than standard PostgreSQL for transactional workloads. Fast, real-time insights, up to 100x faster analytical queries than standard PostgreSQL. AlloyDB AI can help you build a wide range of generative AI applications. AlloyDB Omni is a downloadable edition of AlloyDB designed to run anywhere. Scale up and achieve predictable performance and a high availability SLA of 99.99%, inclusive of maintenance, for your most demanding enterprise workloads. Automated and machine learning-enabled autopilot systems simplify management by handling database patching, backups, scaling, and replication for you.
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