Vertica
| Company type | Subsidiary |
|---|---|
| Industry | Software, Database management |
| Founded | 2005 |
| Founder | Michael Stonebraker, Andrew Palmer |
Key people | Ralph Breslauer (Chairman), Christopher P. Lynch (CEO as of 2010) |
| Products | Vertica Analytics Database, Vertica SQL on Data Lake, Vertica Accelerator |
| Parent | OpenText |
| Website | www |
Vertica is a company specializing in analytic database management software, established in 2005 by database expert Michael Stonebraker alongside founding CEO Andrew Palmer. Subsequent leadership included Ralph Breslauer and Christopher P. Lynch, who assumed the roles of chairman and CEO in 2010 and oversaw Vertica’s acquisition by Hewlett Packard in March 2011.
This acquisition broadened the HP Software suite, focusing on solutions for enterprise and government sectors. After the integration of Micro Focus with Hewlett Packard Enterprise’s Software division, Vertica became a part of Micro Focus in September 2017. Following OpenText’s purchase of Micro Focus in January 2023, Vertica was incorporated into OpenText’s product lineup.
Vertica’s primary offerings consist of the Vertica Analytics Database and Vertica SQL on Data Lake, both tailored to deliver high-speed analytics and big data capabilities for enterprise clientele.
Products
The column-oriented Vertica Analytics Database is engineered to efficiently manage vast and rapidly expanding datasets, delivering swift query responses for data warehouse environments and other applications demanding intensive querying. It offers substantial improvements in query execution compared to conventional relational database systems, ensuring high availability with scalability reaching exabyte levels on commodity enterprise servers. Vertica supports deployment across various cloud infrastructures and Hadoop clusters. Its Eon Mode architecture decouples compute resources from storage, utilizing S3 object storage combined with elastic compute provisioning.
Highlighted features include:
- Column-oriented storage, which enhances sequential data retrieval while compromising transactional tasks such as single-record updates.
- A Massively parallel processing (MPP) design that distributes workloads across nodes to achieve near-linear scalability.
- A standard SQL interface enriched with advanced analytics functions including time series interpolation, event-driven windowing, pattern recognition, statistical methods like regression analysis, and geospatial analysis.
- Embedded machine learning within the database supporting algorithms such as linear regression, logistic regression, k-means clustering, Naive Bayes, random forest, XGBoost, and support vector machine for both regression and classification tasks, enabling model deployment across multiple clusters.
- Efficient data compression through grouping columns of uniform datatype and batching update operations.
- Automated management of workloads, data replication, server recovery, query optimization, and storage efficiency.
- Seamless integration with open source big data technologies including Apache Kafka and Apache Spark.
- Compatibility with common programming interfaces like ODBC, JDBC, ADO.NET, and OLEDB.
- High-speed parallel data transfer capabilities to statistical tools alongside integrated machine learning features.
Vertica’s architecture is purpose-built to enhance query efficiency in data warehousing scenarios while minimizing hardware expenditure.
Since 2011, Vertica has offered a free community edition with limited capacity.
In July 2021, Vertica introduced a cloud-based SaaS solution named Vertica Accelerator, hosted on the Amazon AWS platform.
Optimizations
Vertica was initially developed as the C-Store column-oriented database, an open source academic initiative at MIT and other institutions, first released in 2005.
The platform functions on clusters composed of commodity hardware or commercial cloud environments, and it supports integration with Hadoop, utilizing the HDFS.
In 2018, Vertica launched Vertica in Eon Mode, which decouples compute from storage infrastructure. This design enables flexible scaling of computing power and allows multiple independent sub-clusters to handle diverse workloads while sharing a unified data repository. It operates on shared object storage within cloud settings as well as on object storage-compatible devices in private cloud deployments.
Support for Docker and Kubernetes was introduced in version 10.1.1.
The Vertica Analytics Platform offers compatibility with numerous BI, data visualization, and ETL applications, incorporates Kafka for streaming data ingestion, and rolled out a Spark connector in 2021. Additional integrations include Grafana, Helm, Go, and Distributed R.
Company events
In January 2008, Vertica faced a patent infringement lawsuit filed by Sybase. The company won a preliminary injunction hearing in January 2010, and by June 2010 the case was settled with all allegations dropped.
Starting in 2013, Vertica has organized an annual user conference, presently known as Vertica Unify.