SingleStore raises $80 million to accelerate data analytics with relational databases
December 9, 2020
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Relational database startup SingleStore (previously MemSQL) closed an $80 million funding round today, bringing its total raised to $238 million. The San Francisco-based company plans to use the funds to increase its market presence; expand its engineering team in Portugal, Ukraine, and the U.S.; and grow its customer base internationally. In July, SingleStore partnered with Latin America Business Consulting (LATBC) as the exclusive reseller for its database services in Mexico, Central America, and the Caribbean.

AI and machine learning models require fast databases like SingleStore’s to perform at their peak. Organizations that lack the right technical components in their production pipelines run the risk of failure — according to IDC, 25% of brands already using machine learning report a 50% failure rate. SingleStore aims to prevent this with a platform that serves as the backend for fraud detection, portfolio risk tracking, and even facial recognition apps in industries ranging from financial services to energy, government and the public sector, retail, and ecommerce.

SingleStore — which can be deployed on-premises, as-a-service, or as a hybrid of both — works like most relational databases, which is to say it accepts requests (e.g., for a user, image, video, document, or internet of things events) in the form of queries for data contained within the database. It processes these queries and returns the results in milliseconds, after which it assigns them a score that indicates their overall quality.

SingleStore centralizes data with built-in workflows while performing queries to identify new models. Streaming ingest eliminates the need for data integration tools through built-in batch and real-time pipelines, while the compiling of queries into low-level machine code speeds up responses.

SingleStore can discover anomalies or predict events by combining real-time and historical sources, delivering instant matching to models against datasets. It applies built-in models to maximize response time while scoring models as data is ingested, and it performs ad hoc analysis with business intelligence tools like Tableau, Looker, Microstrategy, and more.

SingleStore can ingest millions of events per day while simultaneously analyzing billions of rows, with support for geospatial data like area, distance, and location analytics and JSON multi-attribute objects. Data can be stored across clusters of machines with transactions written directly to disk or to memory and with compression that optimizes resources for storing up to petabytes of data.

On the redundancy and management front, SingleStore holds a backup copy of data to protect against loss and ensure consistency, and it eliminates duplicate records at the time of ingestion. It also automates common tasks like starting, stopping, restoring, and backing up clusters and provides a monitoring interface to diagnose and assist with query, pipeline, and storage performance tuning by collecting query profiles and exposing potential bottlenecks. Users can manage security configurations by role and group and audit all activities to external secure locations or manage existing account access to enable security tasks like tracking access.

IDC expects the worldwide big data analytics market to be worth $274.3 billion by 2022, and SingleStore is considered among the pack leaders. It saw 70% growth in annual recurring revenue and single-digit cash burn last year, and its customers include Verizon, Intel, Uber, Comcast, Sony, Pandora, and Samsung, among others.

Insight Partners led the Series E round announced today, with participation from new strategic investor Dell Technologies Capital and equity participation from Hercules Capital. Existing investors Accel, Anchorage, Glynn Capital, GV, and Rev IV also participated.

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