ScyllaDB has gained recognition in recent years as a high-performance database solution favored by some of the most demanding organizations worldwide. Prominent users of ScyllaDB include Discord, the social networking service, Expedia, the travel site, and Comcast, a media giant.
In a recent development, ScyllaDB has successfully secured $43 million in a Series C3 funding round, bringing their total funding to $100 million. Leading this funding round were Eight Roads Ventures and AB Private Credit Investors, with participation from TLV partners, Magma Ventures, and Qualcomm Ventures.
ScyllaDB is an open-source NoSQL database initially designed as a drop-in replacement for Apache Cassandra, offering enhanced scalability and performance. Over time, it has also emerged as a strong contender for Amazon DynamoDB. With this fresh injection of funds, ScyllaDB aims to expand its capabilities and compete with the MongoDB database.
Dor Lior, the CEO of ScyllaDB, explained, “We raised the money because we could, not necessarily because it was imperative. We’re making a concerted effort to challenge MongoDB, especially in today’s market climate where efficiency and cost reduction are paramount.”
ScyllaDB offers multiple deployment options, including open source, enterprise, and cloud database-as-a-service choices. The current release, ScyllaDB 5, was introduced in July 2022 and has seen continuous improvements over the past year, resulting in faster database operations. However, the focus is on the upcoming ScyllaDB 6, which is currently in development.
ScyllaDB 6 introduces a groundbreaking concept called “tablets.” Tablets offer a more scalable and rapid method for expanding a database cluster compared to existing NoSQL approaches. They enable the load balancing of a 10-gigabyte chunk of data across available computing resources, making it easier to scale a database for various workloads.
To further enhance elasticity, ScyllaDB 6 incorporates Raft consistent metadata. Raft is an open-source consensus protocol supported by ScyllaDB, ensuring data consistency across distributed clusters. This update allows multiple schema operations and topology changes to occur concurrently, improving scalability.
Notably, while many in the database industry are venturing into supporting vector embeddings for generative AI workloads, ScyllaDB is not pursuing this direction. Lior clarified that ScyllaDB currently focuses on more traditional, non-generative AI use cases, emphasizing that vector support is on their roadmap but not an immediate priority. He cited the challenges of implementing vector search within ScyllaDB’s architecture, highlighting the company’s commitment to maintaining a high level of consistency, which can sometimes make feature implementation more challenging.