FirstMark is an early-stage venture capital firm based in New York City, backing exceptional founders making their mark on the world. FirstMark has proudly invested in founders of remarkable businesses like Pinterest, Shopify, DraftKings, Discord, Airbnb, Stubhub, Riot Games, and dozens more.

FirstMark

Georgian is a fintech company that invests in high growth software companies that harness the power of data in a trustworthy way. They're building a platform to provide a better experience of growth capital to software company CEOs and their teams.  Georgian's platform is designed to identify and accelerate the best growth-stage software companies, taking an intelligent, data-first approach to solving the key challenges CEOs face as they grow their businesses. They invest in companies across North America that harness the power of data in a trustworthy way. Based in Toronto and founded in 2008, Georgian’s team brings together software entrepreneurs, machine learning experts, experienced operators, and investment professionals.

Georgian

Alumni Ventures Group provides high-quality, diversified venture portfolios to individual investors who previously haven't had access to VC. It helps accredited alums from top entrepreneurial schools invest together in the ventures of fellow alums. The firm backs companies with an alumni connection and an institutional lead investor with expertise in the space. AVG also offers focused funds that allow any accredited investor access to a venture portfolio, diversified by type, sector, stage, and geography. Beth Obermiller, Michael Madden, and Mike Collins co-founded the firm in Manchester, New Hampshire in 2013.

Alumni Ventures

Crew Capital is a venture capital firm with a global approach, investing in entrepreneurs with disruptive ideas who solve a real issue, from seed to IPO.  Crew Capital was founded by Daniel Dines - CEO UiPath and Brandon Deer - Chief Strategy Officer UiPath, founders themselves, with entrepreneurship in their blood, in 2020. With more than 40 start-ups in our portofolio, Crew Capital’s goal is to give back to its community and build together with the companies they have invested in the future of tomorrow through technology.

Crew Capital

SurrealDB

SurrealDB is an innovative, multi-model, cloud-ready database, suitable for modern and traditional applications. Its versatility, and focus on developer experience, along with the ability for deployment on cloud, on-premise, embedded, and in edge computing environments, allows developers and organizations to meet the needs of their applications, without needing to worry about scalability or keeping data consistent across multiple different database platforms.

SurrealDB is a multi-model, cloud-native database designed to simplify the development process for modern applications, including web, mobile, serverless, Jamstack, and traditional applications. It combines the database layer, querying layer, API, and authentication layer into a single platform, allowing developers to build secure and performant applications quickly and cost-effectively.

The innovative cost dynamics of serverless computing allow more customers onto the cloud without breaking the bank.

Serverless Computing

SurrealDB is a multi-model database platform that allows developers to store and model data using various techniques, including tables, documents, and graphs. It combines different database types into a single platform, helping enterprises and application developers avoid using multiple systems for different data types.

Data Infrastructure & Analytics

SurrealDB Launches Surreal Cloud, a Fully Managed Database Service That Tackles the Complexity Issues Faced by Developer Teams

SurrealDB is a multi-model, cloud-native database designed to simplify the development process for modern applications, including web, mobile, serverless, Jamstack, and traditional applications. It combines the database layer, querying layer, API, and authentication layer into a single platform, allowing developers to build secure and performant applications quickly and cost-effectively.SurrealDB supports various data models, such as document, graph, relational, and key-value, enabling developers to store and model data using multiple techniques. It offers an SQL-like query language called SurrealQL, which provides querying capabilities, including real-time queries, advanced security permissions for multi-tenant access, and support for performant analytical workloads.In June 2024, the company announced the <a href="https://sp-edge.com/updates/30594">beta launch of Surreal Cloud</a>, a scalable, resilient, cloud-native multi-model database with transparent billing and flexible usage limits.Key customers and partnershipsKey customers include Amazon, CGI, HSBC, NVIDIA, Salesforce, and Samsung.

Triggermesh’s platform allows users to create serverless apps that integrate multiple cloud, data center, and on-premise software and environments, on top of Kubernetes. Through these integrations, the platform aims to break “silos” between enterprise customers and their software development and IT operations (DevOps) teams. The cloud and infrastructure integration development speed is reportedly enhanced by reusing connectors and customizable templates.In March 2022, the platform announced broad support for KNative (an open-source platform to build and deploy serverless workloads) which includes any conformant Knative deployment, along with the provision of Knative distribution. TriggerMesh also announced broad support for creating event-driven architecture that runs on Kubernetes in Google Cloud, to enable users to create integrations to sync data or drive event-driven workloads. Triggermesh went on to launch a service to enable enterprises using Kubeless migrate to Knative in May 2022.

Triggermesh

Iron.io offers multiple tools to assist development operations (DevOps) to focus on core tasks, without managing infrastructure. The company entered the serverless computing market in 2016, with the launch of IronFunctions, effectively an open-source platform that can be used by developers and uses containers as the base. It allows users to launch serverless applications and functions on private and public clouds, on-premise servers, and hybrid environments. IronFunctions can be written in a variety of programming languages including Ruby, PHP, Python, Java, Node.js, Go, and .NET. However, the company currently only provides helper libraries and integration with Amazon Web Services (AWS) Lambda.The company has expanded its operations since 2017 by adding an office in Tokyo, expanding its engineering and customer success teams, and continuing to improve the company’s products (bug fixes, improvements to internal tooling, and adding concurrency graphs, etc.). Iron.io looks to continue ramping up the development of its products by improving performance and reliability and developing a new user interface.Iron.io also continues to invest in new cutting-edge technologies such as “Computerless,” which eliminates the physical machine altogether and allows for it to be fully encapsulated in fiber optic cable.Key customers and partnershipsIts key customers include Google, Harry’s, Philips, Whole Foods, Veritone, and Counsyl.

Iron.io

Elotl offers the “Elotl Milpa” serverless platform to deploy Kubernetes (container orchestration system) apps on the cloud (mainly AWS, Google Cloud, Azure cloud, and Oracle cloud). It allows users to run their Kubernetes workloads in a cost effective manner (around 60%-80% cost savings relative to traditional offerings), avoiding vendor lock-in, Its offering also includes multi-tenancy security.Key customers and partnershipsAs of January 2022, its customers included Robinhood, Ronin, and Symphony, among others.In the year leading to November 2021, deployments through Elotl expanded 5x YoY, and the company became a founding member of the “Mobile Native Foundation” (a space for developers to collaborate on open source projects and discuss topics).

Elotl

ServerlessOps offers DevOps transformation advisory services, focusing on Amazon Web Services (AWS) serverless technology. The firm covers both technical training as well as implementation engineering. ServerlessOps claims it focuses on promoting AWS usage, as it believes AWS Lambda has the best combination of runtime and range of cloud services.

ServerlessOps

Sparta is an open-source framework for building and deploying Go microservices on AWS Lambda-powered microservices. It allows developers to define their application logic, AWS infrastructure, operational metrics, alert conditions, and security policies using Go types within a monorepo. Sparta transforms a Go application into a self-deploying AWS Lambda service, automatically provisioning the required infrastructure through CloudFormation.It integrates with various AWS services, including DynamoDB, S3, Kinesis, SNS, SES, CloudMap, CloudWatch Events, CloudWatch Logs, and Step Functions. It also allows provisioning custom AWS resources and defining IAM roles with limited privileges to minimize the service's attack surface. Sparta emphasizes security and operational best practices as first-class goals.One of Sparta's key features is its ability to discover dynamically created AWS resources at runtime, eliminating the need for hard-coded ARNs in the codebase. This promotes an immutable infrastructure approach. The framework aims to discourage the deployment of monolithic applications as Lambda functions, instead favoring a microservices architecture.

Sparta

This includes all serverless software which does not fall into the other categories but are related to the serverless market (e.g serverless based database providers).

Software and services that monitor, optimize, and enable integrations to improve performance.

Businesses and organizations helping programmers transition to serverless platforms by reducing client dependency on vendor-specific offerings.

Businesses that fill in knowledge gaps between clients and serverless vendors for developing and running complex apps and programs.

Vendor platforms such as AWS Lambda and Azure Functions used by clients to run their program. Effectively the infrastructure for serverless computing.

Serverless database providers offer infrastructure for running Gen AI models

SurrealDB is a multi-model database platform that allows developers to store and model data using various techniques, including tables, documents, and graphs. It combines different database types into a single platform, helping enterprises and application developers avoid using multiple systems for different data types.Developed in Rust, SurrealDB manages security and access permissions, indexing for AI workflows, machine-learning inference, and model processing. Its versatility supports different data requirements, reducing the need for multiple database systems. SurrealDB focuses on easing backend infrastructure management and API creation, promoting faster and more cost-effective development of modern, real-time applications.SurrealDB's architecture is suitable for deployment in cloud, on-premises, embedded, and Edge computing environments. It can operate in single-node or distributed mode, providing high scalability and availability. SurrealDB supports SQL querying from client devices, GraphQL, ACID transactions, WebSocket connections, structured and unstructured data storage, graph querying, full-text indexing, geospatial querying, and row-by-row permissions-based access.Key customers and partnershipsSurrealDB's open-source libraries have gained significant popularity, receiving over 25,000 GitHub stars. This community support has played a key role in SurrealDB's growth.SurrealDB partnered with Docker to leverage Docker's containerization technolog in order to simplify the deployment and scalability of its database platform. This partnership allowed SurrealDB to benefit from Docker's robust infrastructure, enhancing the ease of use and accessibility of its services across various environments, including cloud and on-premises deployments.SurrealDB partnered with Amazon Web Services (AWS) to host its database platform on AWS infrastructure, utilizing AWS' global reach, high availability, and security features. This partnership simplified deployment and management for customers, offering scalable and reliable database solutions. It also integrated SurrealDB with various AWS services, enhancing data flow and ecosystem integration.

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

ANALYST_QUICK_TAKE

PROMINENT_CATEGORY

<div>
 The open-source multi-model database platform, SurrealDB, has introduced Surreal Cloud, a database-as-a-service (DBaaS) solution. It is currently in its beta version, encouraging users to test features and provide feedback for further improvement.
 Along with Surreal Cloud, an AI assistant named Surreal Sidekick has been integrated to aid users by searching through documentation to answer their queries. The service also integrates with Surrealist, a user interface for SurrealDB that allows developers to visually manage their database.
 The company has spotlighted several primary benefits of the platform such as scalability, ACID (atomicity, consistency, isolation, and durability) compliance for multi-row and multi-table transactions, and workload isolation. The last feature permits departments to access shared data without resorting to ETL processes or redundant data marts.
</div> Analyst QuickTake: 
 The product update follows the recent funding round of <a href="https: 
//sp-edge.com/updates/30594"> USD 20 million </a> (Series A) in June 2024, with the funds earmarked to scale SurrealDB's operations and meet the growing demand for its platform that consolidates multiple databases into a single solution, reducing complexity and costs for developers.

SurrealDB

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