![]() The Arrow project provides high-performance building blocks for representing and transporting data used in analytics workflows, and also a multitude of efficient language bindings. Since its origin in 2016, Apache Arrow has quickly emerged as a major building block for modern analytical systems infrastructure - from databases to processing engines. Apache Arrow over the wire for query results In OmniSci 5.5, we added many new features to the query engine focusing both on enterprise readiness and better ecosystem integration. In addition, we made notable performance gains in core query processing and execution - both on CPU and GPU platforms. We also added initial support for parallel executors in the query engine as part of a larger roadmap to better support intensive multi-user workflows. Through releases 5.2 to 5.4, we identified and addressed several intermittent issues related to memory pressure in GPU environments. Looking back at 2020, our engineering team made major strides in improving the robustness, performance and overall enterprise readiness of OmniSciDB, the core analytical SQL engine of the OmniSci platform. Without further delay, let’s dive right in! OmniSciDB This release sets the stage for more innovation in the new year across the entire platform. With several new capabilities in OmniSciDB and immerse, and also a major new OmniSci Render feature. ![]() We’re very happy to announce OmniSci 5.5, our final release for 2020.
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