Elastic Reports 8x Speed and 32x Efficiency Gains for Elasticsearch and Lucene Vector Database
26 Abril 2024 - 5:03AM
Business Wire
The world’s most downloaded vector database is
used by customers to store and search billions of vector
embeddings
Elastic (NYSE: ESTC), the company behind Elasticsearch®, today
announced new vector database performance gains with Elasticsearch
and Apache Lucene, with up to 8x speed and 32x efficiency. These
advancements provide developers with the most flexible and open
tools needed to keep up with rapid generative AI innovation.
New optimization strategies and enhancements driving the
increased gains in Elasticsearch and Apache Lucene include*:
- Multi-threaded search capabilities run searches in
independent segments, minimizing response times, ensuring users
receive their search results as swiftly as possible
- Accelerated multi-graph vector search and information
exchange among segment searches, reducing query latencies up to
60%
- Panama Vector API Integration enabling Java code to
interface seamlessly with SIMD instructions, unlocking a new era of
vector search performance optimization
- Maximized memory efficiency with scalar quantization,
slashing memory usage by approximately 75% without sacrificing
search performance
- Seamless compression improvements that keep search
results accurate while making data smaller, laying the foundations
for binary quantization that will deliver the full potential of
vector search while maximizing resource utilization and
scalability
- Multi-vector integration in Lucene and Elasticsearch
that enables searches across nested documents and joins, making
document searches in Lucene more effective
“Our goal is to make Elasticsearch and Apache Lucene the best
vector database and Elasticsearch the best retrieval platform for
semantic search, RAG, and generative AI use cases,” said Shay
Banon, founder and chief technology officer at Elastic.
“Elastic’s contributions bring multifold performance gains in
speed, scale, and efficiency, ensuring the Elasticsearch-Lucene
integration continues to be a versatile vector database and search
experience loved by developers and trusted by enterprises the world
over.”
Customers are building the next generation of AI enabled search
applications with Elastic’s vector database and vector search
technology. For example, Roboflow is used by over 500,000 engineers
to create datasets, train models, and deploy computer vision models
to production. Roboflow uses Elastic vector database to store and
search billions of vector embeddings.
Learn more about Lucene’s integration into Elasticsearch and how
these investments deliver faster vector search performance and
scale here.
*These features are available in Elasticsearch version 8.10 and
above.
About Elastic
Elastic (NYSE: ESTC), the leading search analytics company,
securely harnesses search powered AI to enable everyone to find the
answers they need in real-time using all their data, at scale.
Elastic’s solutions for security, observability and search are
built on the Elasticsearch platform, the development platform used
by thousands of companies, including more than 50% of the Fortune
500. Learn more at elastic.co.
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