Best Columnar Databases for OpenObserve
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Compare the Top Columnar Databases that integrate with OpenObserve as of June 2026
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This a list of Columnar Databases that integrate with OpenObserve. Use the filters on the left to add additional filters for products that have integrations with OpenObserve. View the products that work with OpenObserve in the table below.
What are Columnar Databases for OpenObserve?
Columnar databases, also known as column-oriented databases or column-store databases, are a type of database that store data in columns instead of rows. Columnar databases have some advantages over traditional row databases including speed and efficiency. Compare and read user reviews of the best Columnar Databases for OpenObserve currently available using the table below. This list is updated regularly.
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Apache Parquet
The Apache Software Foundation
We created Parquet to make the advantages of compressed, efficient columnar data representation available to any project in the Hadoop ecosystem. Parquet is built from the ground up with complex nested data structures in mind, and uses the record shredding and assembly algorithm described in the Dremel paper. We believe this approach is superior to simple flattening of nested namespaces. Parquet is built to support very efficient compression and encoding schemes. Multiple projects have demonstrated the performance impact of applying the right compression and encoding scheme to the data. Parquet allows compression schemes to be specified on a per-column level, and is future-proofed to allow adding more encodings as they are invented and implemented. Parquet is built to be used by anyone. The Hadoop ecosystem is rich with data processing frameworks, and we are not interested in playing favorites.
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