PALO ALTO – Instaclustr, a provider of managed solutions for open source technologies, has raised $15 million from NY-based private equity firm Level Equity. The funding provides Instaclustr with capital to accelerate expansion of its managed platform of core open source technologies. Instaclustr – now serving more than 100 customers from various industries – will double its headcount over the next year. Instaclustr’s revenues have grown 300% over the last 24 months and this pace is expected to continue.
Level Equity joins existing investors Bailador Technology Investments, ANU Connect Ventures, and Our Innovation Fund, LP.
Instaclustr’s Open Source-as-a-Service platform delivers fully hosted and managed big data technology solutions in their 100% open source form, providing customers the data capabilities and reliability required to scale with absolute freedom from vendor or technical lock-in. Core technologies currently provided by the managed platform include Apache Cassandra, Apache Spark and Apache Kafka.
Instaclustr will use this funding to expand its automated and proven management environment for database, analytics, search, and messaging services to include additional open source technologies such as Elasticsearch, Apache Ignite and Apache Flink. The company will also be adding other data-centric open source technologies that integrate well and that are ideally suited for supporting the scale, high availability, and performance demanded from next-gen applications and solutions. All technologies will continue to be made available through a single platform capable of handling customers’ entire data layer.
“We allow customers to get the most production value from an array of powerful open source data solutions – and to do so within a fully managed environment that frees up their IT resources and budget,” said Peter Nichol, CEO, Instaclustr. “The new investment from Level Equity will accelerate our platform’s expansion, grow our sales and support teams, and allow us to reach more organizations seeking to optimize their data-related performance, reliability, security, and scalability.”