Top 68 Big Data Software SaaS Companies in May 2026
As of May 2026, there are 68 SaaS companies in Big Data Software. They have combined revenues of $2.9B and employ 15.4K people. They have raised $4.1B and serve 20M customers combined.
Big Data Software encompasses tools and platforms designed to store, manage, analyze, and visualize large volumes of data that traditional data processing software cannot handle effectively. These solutions enable organizations to derive insights from various data sources, helping in making data-driven decisions. Primary use cases include predictive analytics, operational intelligence, customer behavior analysis, and fraud detection, among others.
Typical features of Big Data Software include data ingestion, storage, processing frameworks, and visualization capabilities. Users range from data scientists and business analysts to IT professionals who are responsible for managing the data lifecycle and ensuring data security. Common buyer personas include professionals from finance, marketing, operations, and research and development, all seeking to leverage big data for enhanced strategic decision-making.
Provider of an open source in-memory data grid platform designed to modernize existing applications. The company's open source in-memory data grid platform with installed clusters offer operational in-memory computing, enabling companies to manage their data and distribute processing using in-memory storage and parallel execution for breakthrough application speed and scale.
Baya Systems accelerates intelligent compute with software-defined fabric solutions for scalable AI and HPC systems. The company allows for creating efficient chips by breaking down complex designs into smaller, modular chiplets, enabling the semiconductor industry to address increasing complexity and decreasing design cycles.
Developer of cloud computing platform intended for provision compute or data storage infrastructure. The company's platform utilizes large amounts of datasets with self-improving algorithms by embedding AI capabilities into their applications via REST API calls, enabling software developers to easily and quickly discover and embed AI algorithms in their applications.
Neysa is an AI Acceleration Cloud System provider that democratizes AI adoption with purpose-built platforms and services for AI-native applications. It empowers businesses to discover, deploy, and scale Gen AI and AI use cases securely and cost-effectively.
Ververica, the original creators of Apache Flink®, empowers businesses with high-performance data streaming and processing solutions. Streamlining operations, developer efficiency, and enabling customers to solve real-time use cases reliably and securely. Ververica’s Unified Streaming Data Platform, powered by its cloud native VERA engine, revolutionizes Apache Flink®, making it easy for organizations to harness data insights at scale. With Ververica, customers can meet any business SLA, leveraging advanced data streaming and processing capabilities in real-time or on the lakehouse. Ververica enables businesses to connect, process, govern, and analyze data, across infinite use cases, with flexible deployment options, including public cloud, private cloud, or on-premise environments. Discover more at ververica.com.
Arcee AI is building the next generation of foundation models and tooling for enterprise and industrial-scale AI. Its AFM family of foundation models and vertically-integrated stack help businesses deploy secure, controllable, and cost-effective AI at the edge, in the cloud, or anywhere in between.
Provider of cloud computing and large data technology services. The company uses IaaS infrastructure to provide customers with deep customized PAAS/SAAS products and services.
Developer of a software platform designed to bring the power of cloud computing to engineering applications. The company's software platform offers an online community and marketplace enabling engineers, scientists and their service providers to discover, try and buy ubiquitous computing services on demand, in any private, public or hybrid cloud and get a performance boost of 10x or more when running their complex mathematical models and simulations.
Developer of cloud orchestration and workload scheduling platform designed to simplify and speed up cloud rendering and management. The company's advanced machine learning-based platform harnesses underutilized computer power and multiple clouds to predict the compute resources needed to execute complex computational workloads with accelerated computing, accuracy and speed, enabling entertainment studios and financial services firms to access computer power on-demand without fixed investments., Accelerates applications in the cloud
Revenue
$5.4M
Customers
30
Year founded
2015
Funding
$11.1M
Team size
22
Growth
37.53%
Inclusion Criteria
- Product must be capable of handling and processing large volumes of structured and unstructured data.
- Must provide advanced analytics features such as machine learning or predictive modeling.
- Should include data visualization tools to present insights clearly and effectively.
- Must support integration with various data sources and formats.
- Not just data storage; must also offer actionable insights and analytics capabilities.
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