Search Results for "processing"

pg_analytics (formerly named pg_lakehouse) puts DuckDB inside Postgres. With pg_analytics installed, Postgres can query foreign object stores like AWS S3 and table formats like Iceberg or Delta Lake. Queries are pushed down to DuckDB, a high-performance analytical query engine. By transforming Postgres into a performant search and analytics engine, ParadeDB frees your team from the pain of scaling and syncing Elasticsearch.

GreptimeDB treats all time series as contextual events with timestamps, and thus unifies the processing of metrics, logs, and events. It supports analyzing metrics, logs, and events with SQL, PromQL, and streaming with continuous aggregation. GreptimeDB is a time-series database optimized for storing and querying large amounts of time-series data, commonly used in monitoring and IoT applications.

Lantern is a real-time data transformation engine that enables data engineers to build, run, and monitor streaming data pipelines with SQL. It’s designed to process events in motion, offering low-latency stream transformations, aggregations, and enrichment in a declarative way. Lantern is especially suited for modern data infrastructure and analytics platforms.

...In particular, IndraDB emphasizes simplicity of implementation and query semantics, and is similarly designed with the assumption that it may be representing a graph large enough that full graph processing is not possible. IndraDB departs from TAO (and most graph databases) in its support for properties. IndraDB offers a variety ways to work with it: as a server with cross-language support, as a rust library, and via CLI. What follows are a few examples of each use case.