The 10 Hottest Big Data Startup Companies Of 2018

Demand for big data and business analytics solutions is expected to generate $260 billion in revenue by 2022 and that industry growth is spurring a steady stream of startups developing innovative big data products.

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See the latest entry: The 10 Hottest Big Data Startups of 2022

The demand for big data technologies continues to explode with worldwide revenue from big data and business analytics solutions expected to reach $166 billion this year – up 11.7 percent from 2017 – and hit the $260 billion mark in 2022, according to market researcher IDC.

So it's no surprise that a steady stream of young companies continues to develop innovative big data products to meet the needs of data managers, data scientists, data analysts and others, offering leading-edge technology for data management, data accessibility, data connectivity and data quality.

Here's a look at 10 big data startups that caught our attention in 2018.

Data Artisans

Top Executive: Kostas Tzoumas, CEO and Co-Founder

Businesses are increasingly finding themselves processing and analyzing live, streaming data in real time.

Data Artisans was founded in 2014 by the creators of Apache Flink, the open-source software framework and distributed processing engine for stateful computations using streaming data. The Berlin, Germany-based company's Apache Flink-powered platform makes it possible to build and run streaming applications in a secure, scalable, frictionless and cost-efficient manner.

This year, the company expanded its product lineup with the Data Artisans Streaming Ledger software, which makes it possible to process serializable ACID transactions using streaming data. Until now it has been difficult to apply ACID (atomicity, consistency, isolation and durability) standards, which guarantee data integrity in distributed transactions, to streaming data processing.

dotData

Top Executive: Ryohei Fujimaki, CEO

As big data volumes grow, data science -- the interdisciplinary set of processes used to extract insights from data -- becomes more complex. That can mean it takes more time for businesses to derive value from their data assets.

NEC Corp. spinoff dotData is addressing that problem with an end-to-end, AI-powered data science automation platform that's designed to reduce the time needed to complete complex data science projects. The Cupertino, Calif.-based dotData unveiled release 1.2 of the dotData Platform at Oracle OpenWorld in October with new attribute features, enhanced model operations, and new feature and model insights.

Dremio

Top Executive: Tomer Shiran, CEO and Co-Founder

Making data accessible to everyday information workers remains one of the biggest big data challenges. Dremio develops a Data-as-a-Service platform the company says bridges the gap between data engineers and data consumers. The system allows users to curate data scattered across disparate sources, providing an SQL interface between popular BI tools like Tableau, QlikView and Looker, and the ever-proliferating number of relational databases, NoSQL databases and data lakes.

Earlier this year, Dremio -- founded in 2015 and based in Mountain View, Calif. -- raised $25 million in Series B financing, bringing its total funding to $40 million. In October, the company introduced Dremio 3.0 with a collaborative data catalog, end-to-end data encryption and new controls for multi-tenant deployments.

Gluent

Top Executive: Tanel Poder, CEO and Founder

Gluent takes the position that an organization's valuable data assets shouldn't be locked up in relational database silos. The company's Gluent Data Platform offloads data – "liberates" it, according to the company – from traditional relational database management systems and moves it to Hadoop where it can be more easily accessed from across an enterprise. The company also offers Gluent Cloud Sync for migrating Hadoop tables to the cloud.

In October, Dallas-based Gluent, founded in 2014, debuted a new release of the Gluent Data Platform with additional insights into virtualized relational database tables and new data discovery and lineage functionality.

Immuta

Top Executive: Matthew Carroll, CEO and Co-Founder

Immuta has created a data management platform specifically for data science tasks, making it easier for data scientists to find and manage the data they need to develop the data models used to power business analytics, machine-learning and AI tasks.

Founded in 2014 and based in College Park, Md., Immuta launched its inaugural channel program in March, seeking reseller, professional services, IT infrastructure and technology partners to work with the Immuta platform for data science tasks.

Magnitude Software

Top Executive: CEO Chris Ney

Magnitude Software, founded in 2014 and based in Austin, develops a series of enterprise information management, data connectivity and business intelligence software.

In September, the company debuted the Magnitude Gateway, a universal data connectivity platform that provides immediate access to operational and analytical data wherever it resides, including relational databases, NoSQL databases and Software-as-a-Service applications.

Naveego

Top Executive: Katie Horvath, CEO

Naveego's mission is to fix data accuracy problems, helping businesses and solution providers transform raw data into actionable information assets. The company, founded in 2014 and based in Traverse City, Mich., offers master data management and data quality management software tools for synchronizing and cleaning up huge volumes of data scattered across disparate systems.

In October, Naveego unveiled the 2018.2.0 release of its Complete Data Accuracy Platform with new features and capabilities for big data ingestion and storage, data flow logging, auto-provisioning and self-service, and master data management scalability.

Octopai

Top Executive: Amnon Drori, CEO and Co-Founder

Metadata is often scattered across multiple, disparate systems, forcing business intelligence groups to use multiple tools, which often require special development and customization, to find the data they are looking for.

Octopai markets an automated, centralized, cross-platform metadata management and data lineage search engine that business intelligence organizations use to quickly discover and govern shared metadata.

Earlier this year Octopai, founded in 2015 and based in Rosh Ha'ayin, Israel, was named one of 10 cloud-based startups to participate in Microsoft's ScaleUp 2018 program, a four-month program that provides startups with tools, resources, connections, knowledge and expertise to more quickly grow their business.

Timescale

Top Executive: Ajay Kulkarni, CEO and Co-Founder

Managing times-series data, such as that generated by financial service systems or Internet of Things networks, can be a challenge. Timescale has developed TimescaleDB, a time-series database that is optimized for fast data ingestion and complex queries.

TimescaleDB 1.0 launched in September. Based on the open-source PostgreSQL database, TimescaleDB can scale to 100-plus billion rows of data on a single server with time-series functionalities, an optimized query engine and automatic partitioning.

New York-based Timescale was founded in 2015.

Unravel Data

Top Executive: Kunal Agarwal, CEO

Big data systems often have many moving parts. Unravel Data offers application performance management tools used to collect and analyze performance data from big data applications and infrastructure, using the results to troubleshoot and optimize the performance of big data systems.

Founded in 2013 and based in Menlo Park, Calif., Unravel Data raised $15 million in Series B funding in January.

Unravel Data works with platform vendors such as Cloudera and Microsoft Azure, consulting partners including Capgemini and HCL, and technology partners like Arcadia Data and Qubole.