Analyze billions of rows in milliseconds
Get faster analytics and lower data processing costs with a true in-memory columnar analytics database trusted by the world’s most regulated companies.
Reduce the cost and complexity of your data infrastructure without sacrificing performance
Backed by patented technology and built for performance and scalability, Vector uses a distributed and columnar engine with parallel query processing that allows customers to store more data and analyze it faster.
Vectorized processing
SIMD vectorization for faster analytical queries.
CPU cache as execution memory
100x faster than RAM to execute without lags.
Multicore parallelism
Maximize concurrency while enabling load prioritization.
Data lake ingestion
Easily load CSV, Parquet and ORC files through External Tables into Vector.
Pure column store
Zero penalty real-time data retrieval and updates.
Smart compression
Maximize throughput for real-time applications.
Real-time data analytics simplified
Vector can support any workload or analytics use case with millisecond latency and zero performance bottlenecks. Deploy on-premises, and on AWS, Azure, and Google Cloud with little or no database tuning.
Maximum performance, speed, and scalability
Process queries on historical and real-time data with sub-second and millisecond response times so you can make fast, informed decisions with confidence.
Support for complex and diverse workloads
Store and query data outside of traditional structures so you can work with diverse data formats, sizes, and analytical workloads effortlessly.
Enterprise-class security and compliance
Operate in the toughest data environments with encryption at rest and in transit, and dynamic data masking to govern and secure your data.
Deliver zero penalty real-time updates
Make complex data analysis simple with Vector.
Fast, feature-rich, and easy to use
Enjoy all of the must-have features for advanced analytical capabilities along with simplicity, speed, and scale. Database admins will love the fast implementation. Just download and set up.
Performant
MPP architecture results in increasing scalability and performance of queries and supports more complex analytics tasks.
Auto partitioning leads to faster query execution and better resource management, allowing users to focus on analysis rather than database tuning.
Automatic storage indexes enable typical OLAP queries to access only a fraction of the full data set, significantly improving query performance.
Versatile
Spark UDFs to enable advanced data transformations and analytics.
REGEX pattern matching allows for more advanced search functionalities, enabling users to efficiently handle complex queries and improve data retrieval accuracy.
Advanced external tables allow users to perform complex and customized data operations directly within their analytics workflows.
Secure
Protect sensitive data with encryption at rest and in transit with the ability to re-key the database with new encryption keys.
Dynamic data masking and column-level de-identification provide a safe way to share data across stakeholders.
Phased, non-disruptive migrations move suitable workloads to the cloud while those that should remain on-premises run on amortized infrastructure for lower TCO.
See Actian Vector in Action
Actian Vector experts can help you establish the right data foundation to unlock the full potential of your data for real-time analytics. Get in touch to see how we can support a wide range of analytic use cases across every industry.