Best OLAP Databases for Apache Airflow
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Compare the Top OLAP Databases that integrate with Apache Airflow as of June 2025
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This a list of OLAP Databases that integrate with Apache Airflow. Use the filters on the left to add additional filters for products that have integrations with Apache Airflow. View the products that work with Apache Airflow in the table below.
What are OLAP Databases for Apache Airflow?
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 Apache Airflow currently available using the table below. This list is updated regularly.
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1
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 -
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Apache Druid
Druid
Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures.
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