There is plenty about human beings that can be lauded, but at the same time, nothing would deserve the honor more than our ability to improve at a consistent pace. We say this because the stated ability has already fetched the world some huge milestones, with technology appearing as a rather unique member of the group. The reason why technology’s credentials are so anomalous is purposed around its skill-set, which was unprecedented enough to realize all the possibilities for us that we couldn’t have imagined otherwise. Nevertheless, a closer look should be able to reveal how the whole runner was also very much inspired by the way we applied those skills across a real world environment. The latter component was, in fact, what gave the creation a spectrum-wide presence and made it the ultimate centerpiece of every horizon. Now, having such a powerful tool run the show did expand our experience in many different directions, but even after reaching so far ahead, this prodigious concept called technology will somehow keep on delivering the right goods. The same has grown to become a lot more evident in recent times, and assuming one new HRM-themed development pans out just like we envision, it will only propel that trend towards greater heights over the mear future and beyond.
SingleStore, a company that allows you to transact, analyze and contextualize data, has officially announced the launch of powerful new capabilities to accelerate the development of AI, analytics, and other applications, becoming industry’s only real-time data platform. According to certain reports, the stated update will see SingleStore introducing ground-breaking features like indexed vector search, an on-demand compute service for GPUs/ CPUs, a new free shared tier, and more. Although slightly different in their make-up and core function, all these features will work to cut back on long development cycles, while simultaneously providing the performance and scale that customers need for building comprehensive applications. But how will the promised new innovations function on a more actionable level? Well, beginning from indexed vector search, the solution leverages Approximate Nearest Neighbor (ANN) vector indexing algorithms to generate 800-1,000x faster vector search performance than precise methods (KNN). Furthermore, given that we have in play both full-text and indexed vector search capabilities, users will be able to access true hybrid search which takes advantage of the full power of SQL for queries, joins, filters and aggregations. Owing to this value proposition, SingleStore can comfortably claim to be a better alternative, in comparison to those more-prevalent vector-only databases that require niche query languages and are not designed to meet enterprise security and resiliency needs. Next up, we must get into the new on-demand compute service for GPUs and CPUs. The idea here is to deliver a kind of compute service which works alongside SingleStore’s native Notebooks, thus enabling developers to spin up GPUs and CPUs and run database-adjacent workloads, including data preparation, ETL, third-party native application frameworks, etc. Bringing compute to algorithms rather than the arrangement being completely opposite, this maneuver on SingleStore’s part should go a long way to help developers community build high performing AI applications in a safe and secure manner, and guess what, they also won’t require any unnecessary data movement to get the job done.
Then, we have the prospect of new CDC capabilities targeted towards data ingest and egress. These CDC capabilities will primarily hope to reduce the cost and operational burden of moving data in and out of SingleStore’s ecosystem, doing so through real-time Change Data Capture (CDC) in for MongoDB®, MySQL, and ingestion from Apache Iceberg. Again removing the hassle of any extra effort, one can achieve the promised objective without the help from other third party CDC tools. In case that doesn’t sound like enough, then we must mention how SingleStore can now also support CDC out capabilities that ease migrations, and at the same time, enable the use of its platform as a source for other applications and databases, such as data warehouses and lakehouses. Moving on, another thing which this whole development brought up to the fore was the wider availability of SingleStore Kai. First announced back in 2023, SingleStore Kai is basically an API which can deliver 100 times faster analytics on MongoDB®, and to realize that, it never asks for a single query change or data transformation. Now understandably ready for both analytical and transactional processing of apps built on MongoDB, the solution in question can also support BSON data format natively, deliver improved transactional performance, showcase similar performance quality for arrays, and offer industry-leading compatibility with MongoDB query language.
“Our new features and capabilities advance SingleStore’s mission of offering a real-time data platform for the next wave of gen AI and data applications,” said Nadeem Asghar, SVP of Product Management and Strategy at SingleStore. “New features, including vector search, Projections, Apache Iceberg, Scheduled Notebooks, autoscaling, GPU compute services, SingleStore Kai™, and the Free Shared Tier allow startups — as well as global enterprises — to quickly build and scale enterprise-grade real-time AI applications. We make data integration with third-party databases easy with both CDC in and CDC out support.”
Hold on, there are still a few more bits left to unpack, considering we still haven’t discussed the newly-introduced Projections that aid SingleStore’s stature as the world’s fastest HTAP database. You see, these Projections make it possible for developers to speed up range filters and group by operations using secondary sort and shard keys. To give you a lowdown on the expected improvement, query performance improvements are likely to stretch across 2 to 3 times or more, depending on the size of the table. Finally, rounding up the highlights is a free shared tier, which is there to help startups and developers bring their ideas to life at no financial cost whatsoever.
The development delivers a rather intriguing follow-up to SingleStore’s recent growth which saw it exceeding $100M in ARR late last year. This growth also showed up big time when it was ranked #2 in the emerging category of vector databases, and got recognized by TrustRadius as a top vector database in 2023. It gets better, as around that time only the company even won InfoWorld’s Technology of the Year award in the database category.
“We believe that a data platform should both create new revenue streams while also decreasing technological costs and complexity for customers. And this can only happen with simplicity at the core,” said Raj Verma, CEO of SingleStore. “This isn’t just a product update, it’s a quantum leap… SingleStore is offering truly transformative capabilities in a single platform for customers to build all kinds of real-time applications, AI or otherwise.”
Founded in 2011, SingleStore’s rise stems from an ability to offer streaming data ingestion, support for both transactions and analytics, horizontal scalability, and hybrid vector search capabilities. Across these services, the company has proven to deliver 10 to100 times better performance at literally 1/3 of the costs, if pitted against legacy architectures. The company’s excellence in what it does can also be understood once you consider it serves customers throughout the world, including Fortune 500 companies and global data leaders. Some of SingleStore’s clients happen to be Comcast, Cisco, Disney, Dell, Heap, Hulu, Siemens, Kellogg’s, Adobe, fiverr, and many others.
“At Adobe, we aim to change the world through digital experiences,” said Matt Newman, Principal Data Architect at Adobe. “SingleStore’s latest release is exciting as it pushes what is possible when it comes to database technology, real-time analytics and building modern applications that support AI workloads. We’re looking forward to these new features as more and more of our customers are seeking ways to take full advantage of generative Al capabilities.”
