Lightspeed Venture Partners is a venture capital firm that engages in consumer, enterprise, technology, and cleantech markets. It focuses on seed, early-stage, later-stage, expansion-stage, start-ups, growth companies, and incubation, and specializes in debt financing for start-ups and growth companies. Lightspeed Venture Partners invests in various sectors that include enterprise, consumer, big data, bitcoin, enterprise technology, cleantech, mobile, internet, financial technology, cloud solutions, e-commerce, storage, media, networking, energy, and software, software-as-a-service, information technology, biotechnology, and social.

Lightspeed Venture Partners

Kleiner Perkins is a venture capital firm specializing in investing in early-stage, growth, and incubation companies. The firm continues that legacy, investing in founders with bold ideas that span industries and continents, partnering with them from inception to IPO and beyond to maximize the potential of their ideas. They also focus on early computer firms using their devices and programming and service companies. It also invests in the digital, life sciences, and healthcare industries.

Kleiner Perkins

Redpoint has partnered with visionary founders to create new markets and redefine existing ones since 1999. The firm invests in startups across seed, early, and growth phases. In total, Redpoint manages $4 billion across multiple funds.

Redpoint

Materialize

Materialize is a streaming SQL database company that makes it easy for developers to understand streaming data, answer complex questions, and build intelligent applications using standard technology. Materialize allows users to ask questions about their data, and then get low-latency results even as the underlying data changes and keeps the results of the queries and incrementally updates them as new data comes in. The company was founded in 2019 and is headquartered in New York.

Materialize is a streaming database that enables real-time data processing through standard SQL queries. The platform maintains continuously updated query results as new data arrives, eliminating the need to recompute queries repeatedly. Built on top of Timely Dataflow and Differential Dataflow frameworks, Materialize processes streaming data incrementally, updating only what changes rather than recalculating entire datasets. The platform presents itself as a PostgreSQL-compatible database with full ANSI SQL support, allowing users to create materialized views that are automatically kept up to date as source data changes. Through its cloud-native architecture, Materialize provides separation of storage and compute, strict serializability for data consistency, horizontal scalability, and workload isolation. The platform can ingest data from multiple sources including Kafka, PostgreSQL Change Data Capture, Redpanda, event streams, and data lakes. Users can perform complex transformations including multi-way joins, aggregations, and analytics with millisecond-level query latency. In October 2022, Materialize launched its distributed streaming database as a fully-managed cloud service, featuring elastic storage on AWS S3 and active replication capabilities.

Data Infrastructure & Analytics

Materialize Raises $60M to Make Streaming Data Accessible to Businesses Just Using SQL

Materialize is a streaming database that enables real-time data processing through standard SQL queries. The platform maintains continuously updated query results as new data arrives, eliminating the need to recompute queries repeatedly. Built on top of Timely Dataflow and Differential Dataflow frameworks, Materialize processes streaming data incrementally, updating only what changes rather than recalculating entire datasets. The platform presents itself as a PostgreSQL-compatible database with full ANSI SQL support, allowing users to create materialized views that are automatically kept up to date as source data changes. Through its cloud-native architecture, Materialize provides separation of storage and compute, strict serializability for data consistency, horizontal scalability, and workload isolation. The platform can ingest data from multiple sources including Kafka, PostgreSQL Change Data Capture, Redpanda, event streams, and data lakes. Users can perform complex transformations including multi-way joins, aggregations, and analytics with millisecond-level query latency. In October 2022, Materialize launched its distributed streaming database as a fully-managed cloud service, featuring elastic storage on AWS S3 and active replication capabilities.
Key customers and partnerships
Materialize integrates with tools in the PostgreSQL ecosystem and platforms like dbt for analytics engineering workflows.

Streaming Database Overview: Use cases, architectures, and trade-offs | Materialize

Taming the beast that is a SQL database

How we built the SQL Shell

A glimpse into the world of cloud native streaming databases with Materialize

Rise of the Streaming Databases — Episode 1: Materialize

Developing SQL-Based Streaming Data Apps with Arjun Narayan of Materialize

Materialize- The Streaming Database on the SQL Platform

The Cloud Operational Data Store

Materialize offers early release of its streaming database as a service

Time Data Streaming Databases

Materialize Announces New Distributed Streaming Database

Materialize’s ‘distributed database’ mobilizes streaming data with the simplicity of SQL

Materialize: Managed Real-Time Data

Materialize Makes Using Real-Time Data as Simple as Batch With New Distributed Streaming Database

Fivetran is a cloud-based automated data integration platform that enables businesses to move data from various sources, including SaaS applications, databases, and files, into data warehouses, data lakes, and other destinations. The company's platform offers multiple deployment models to meet diverse business needs, ranging from stringent security requirements to maintaining on-premises databases even after partial cloud migration.The company's data movement platform is designed to automate and streamline the process of extracting, loading, and transforming (ELT) data, empowering organizations to focus on data-driven insights and decision-making. With real-time analytics, database replication, AI workflows, and cloud migrations facilitated by Fivetran, thousands of customers worldwide can leverage the platform to drive business growth.Fivetran's core offering revolves around its connector library, which supports over 500 data sources, including SaaS applications, databases, ERPs, and files. These connectors enable automatic, reliable, and secure data movement, regardless of whether the data resides on-premises, in the cloud, or in a hybrid environment. The platform's scalable architecture allows businesses to seamlessly add or remove data sources as their needs evolve.To enhance the usability and accessibility of the ingested data, Fivetran employs a normalized schema approach. By delivering data in a normalized format, the platform enables customers to remix and reshape the data according to their specific requirements, facilitating efficient data analysis and reporting. Additionally, Fivetran offers pre-built data models and dbt Core integration, empowering customers to create analytics-ready tables tailored to their business use cases, such as analyzing deal opportunities from Salesforce, generating general ledger reports from QuickBooks data, or evaluating return on ad spend across advertising platforms.In <a href="https://sp-edge.com/updates/30203">June 2024</a>, the company launched Managed Data Lake Service to simplify the process of managing data lakes for businesses of any size. Key benefits include the ability to centralize data for insights and convenience. Furthermore, it reduces costs by discontinuing support for legacy data warehouses.In September 2024,&nbsp;<a href="https://sp-edge.com/updates/33748">Fivetran introduced "Hybrid Deployment",</a> allowing customers to run data pipelines within their environment while managing them through Fivetran's platform. This solution enables enterprises to securely centralize data from various sources, including cloud-based SaaS apps and legacy databases. Fivetran claims Hybrid Deployment offers full visibility of all pipelines from a single interface, enhanced data security, and simplified setup and maintenance.Key customers and partnershipsOver the years, Fivetran has attracted a diverse range of customers across various industries, including ecommerce, finance, technology, and media. Notable clients include Autodesk, Conagra Brands, JetBlue, Lionsgate, Morgan Stanley, and Ziff Davis, among others. These companies leverage Fivetran's platform to streamline their data integration workflows, optimize their analytics capabilities, and gain a competitive edge through data-driven decision-making.To further enhance its offerings and enable seamless integrations, Fivetran has established strategic partnerships with various technology providers, including data warehousing solutions, cloud platforms, and business intelligence tools. For instance, Fivetran collaborates with Databricks, enabling customers to build an open lakehouse with Delta Lake powered by the Databricks Data Intelligence Platform. Additionally, Fivetran's integration with Unity Catalog provides out-of-the-box governance and security for Fivetran-generated tables.

Fivetran

<div>
 
 Domo is a cloud-based analytics platform that enables businesses to connect, transform, and visualize data from various sources. It provides a comprehensive solution for data management, analysis, and visualization, empowering organizations to make data-driven decisions. Domo's platform is designed to foster collaboration, efficient decision-making, and improved business outcomes through its user-friendly interface and powerful data manipulation capabilities.
 
 
 Domo's key offerings include data integration, data warehousing, business intelligence (BI), and intelligent applications. The platform leverages its Adrenaline engine and offers over 1,000 pre-built connectors to extract data from cloud applications, databases, spreadsheets, and other sources. This data is then stored in Domo's internal data warehouse or accessed through federated queries, enabling users to analyze and visualize it using Domo's extensive collection of visualization tools and dashboards.
 
 
 Domo&rsquo;s user experience is designed to be intuitive and accessible, fostering high adoption rates across organizations. Its user-friendly interface, seamless collaboration features, and mobile-first approach contribute to its widespread adoption and ease of use. Domo's platform is built for speed and scalability, allowing organizations to quickly access and analyze even large datasets without experiencing performance issues.
 
 
 Key customers and partnerships
 
 
 Domo serves over 2,300 customers across various industries, including major enterprises such as eBay, Walmart, Cisco, Citibank, HP, The National Geographic Society, Verizon, US Army, Vanguard, Microsoft, IBM, Thomson Reuters, Airbus, Orange, AT&amp;T, Caterpillar, Volvo Cars, and Comcast.
 
 
 The platform has been widely adopted by organizations seeking to leverage data for better decision-making, improved customer insights, and enhanced marketing analytics. Domo has formed strategic partnerships with companies like Regional One Health and Torchy's Tacos, enabling them to leverage Domo's capabilities for healthcare metrics and finance applications, respectively.
 
</div>

Domo

Founded in 2014, Confluent, Inc. is a technology company headquartered in Mountain View, California. The company specializes in data streaming platforms, primarily based on Apache Kafka, an open-source project created by Confluent's founders while working at LinkedIn. Confluent offers two main products: Confluent Platform, an on-premise solution, and Confluent Cloud, a fully managed SaaS. These products help organizations harness real-time data streams for various applications, including microservices, Internet of Things (IoT), financial services, fraud detection, and customer analytics.Confluent's primary offering in data infrastructure services is its integration solution, which enables organizations to unify data from disparate sources. The Confluent Platform and Confluent Cloud act as clients' central nervous systems, allowing them to connect various IT systems and applications to capture and process real-time data streams. This capability enables businesses to make decisions based on continuously flowing data.In September 2024,&nbsp;<a href="https://sp-edge.com/updates/33818">Confluent announced upgrades to its Confluent Cloud</a> product, enhancing support for Apache Flink. The updates include support for the Table API, simplifying development for Java and Python users, and private networking support to improve data security. These upgrades aimed to simplify Flink deployments, enhance security, and make it easier for organizations in regulated industries to stream data and integrate it into applications.Key customers and partnershipIn December 2023, Confluent expanded partnerships with MongoDB, Pinecone, Rockset, Weaviate, and Zilliz as part of its "Data Streaming for AI" initiative. These partnerships aimed to provide real-time contextual data from Confluent's platform to partners' vector databases, facilitating the development of AI-powered applications.

Confluent

<div>
 
 dbt Labs provides an open source data transformation tool that uses analytics engineering. It is aimed at programmers with knowledge of SQL to develop models with SELECT statements, test and document each model, and install safely with Git-enabled version control. The software enables the user to develop faster, work from the same assumptions, deploy with confidence, and&nbsp; ensure low risk with governance and safety. The company also offers dbt Core, which is an open source software for analytics engineers, and dbt Cloud Enterprise for secure, reliable access to data. JetBlue and Domain are some of its clients.
 
 
 
</div>

dbt Labs

Starburst provides an analytics engine that enables organizations to access and analyze distributed data without moving it from its source location. The company's platform is built on Trino (formerly known as Presto), a distributed SQL query engine designed for running interactive analytics queries across various data sources. The platform allows users to query data across multiple databases, data lakes, and data warehouses simultaneously, eliminating the need for costly and time-consuming data centralization. In February 2023, Starburst introduced Warp Speed, a smart indexing and caching solution that accelerates queries up to 7x faster by autonomously identifying and caching frequently used data. The company's software includes two main offerings: Starburst Enterprise for self-managed deployments and Starburst Galaxy, a Software-as-a-Service (SaaS) solution launched in 2021 that enables data lake and cross-cloud analytics. In February 2022, Starburst reported tripling its customer base and annual recurring revenue in the previous 12 months.
Key customers and partnerships
Starburst's platform is used by organizations including Zillow, Standard Chartered, Carrefour Brazil, Comcast, DoorDash, VMware, and Condé Nast. The platform helped Priceline reduce data storage costs by 5-10x while AssuranceIQ achieved a 10% increase in conversion rates. Starburst had established partnerships with major cloud platforms including AWS, Azure, Google Cloud Platform, Alibaba Cloud, Red Hat, and HPE. The company also partnered with Red Hat as one of the inaugural members of the Red Hat OpenShift Data Science ecosystem.

Starburst

Solutions to unify data from disparate sources by extracting, transforming, loading, and storing data in a usable form (such as in data warehouses) for further analysis.

Tools to monitor data for quality issues in real-time, as it moves throughout the data pipeline.

Providers of storage solutions that help accelerate data analytics. These include primary storage solutions, such as data warehouses and data lakes, and secondary storage solutions for non-mission-critical data.

Solutions that enable businesses to carry out data processing and create ML models on the underlying data for predictive analysis.

Tools for enterprises to visualize data in a graphical form and obtain insights on the same using AI and natural language processing.

Companies that use GenAI as a core part of their product offering for data infrastructure & analytics.

Leverages GenAI to help organizations extract insights and supports GenAI application development through data preparation

Offers data analytics and storage platforms for business under a B2B SaaS model

These are tools that help prepare data for AI/ML applications

Materialize

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