Data is one of the world's greatest resources, powering everything from video recommendation engines and digital banking to the burgeoning AI revolution. But in a world where data is increasingly distributed across locations—from databases to data warehouses to data lakes and more—combining it into a compatible format for use in real-time scenarios can be a daunting task.
Applications that do not require instant access to real-time data can simply combine and process data in batches at fixed intervals. This "batch data processing" can be useful for things like processing monthly sales data. But often a business needs real-time access to data as it's being created, and this could be critical to data management software. based customer service in current information about each and every sale, for example. Elsewhere, transportation applications also need to process all sorts of data points to connect a passenger with a driver; this is not something that can wait a few days. These kinds of scenarios require what's known as "stream data processing," where data is collected and combined for real-time access, something that's much more complex to set up.
And this is something that Dozer it sets out to address, powering fast read-only APIs directly from any source via a plug-and-play data infrastructure backend.
Dozer is the work of Vivek Guadapuri y matthew pelati, who founded the company from its Singapore base nearly a year ago. The duo have built a distributed team of 10 across Asia and Eastern Europe as they prepare to expand beyond the current product. The available fonts (i.e. not quite open source) offers a fully monetizable product.
Dozer has been testing its product with a handful of undisclosed design partners, and today it's emerging from stealth for any developer to access. The company also revealed that it has raised $3 million in seed funding from Sequoia Capital (through his program Increased ), of Google, gradient y January Capital.
Large coverage
There are already countless tools designed to transform, integrate, and leverage distributed data, including streaming databases and ETL (extract, transform, load) tools such as Apache Flash, Airbyte and Fivetran; caching layers for transient data storage like Redis; and instant APIs powered by Hasura or Supabase to funnel data between systems.
Dozer, for its part, works across all of these various categories, taking what it believes are the best bits and removing the friction that comes with building the infrastructure and pipelines that support real-time data applications.
Users connect Dozer to their existing data stack, which can include databases, data warehouses, and data lakes, and Dozer takes care of extracting, caching, and indexing data in real time, and displays it via low-latency APIs. So while solutions like Airbyte or Fivetran help get data into a data warehouse, Dozer focuses on the other side: "making this data accessible in the most efficient way," Gudapuri explained.
Gudapuri said Dozer "takes a dogged approach," one that tackles very specific problems and nothing more. For example, the databases Existing streaming solutions solve many problems well beyond what Dozer offers, which is all about providing real-time data updates and APIs in a single product.
“We solve just the right amount of issues in each of these categories to deliver a fast build experience for developers, as well as performance out of the box,” Gudapuri said. "Developers (currently) have to integrate various tools to achieve the same thing."
As an example, an existing streaming database will likely attempt to present the full database experience to the user, query engine, data exploration, OLAP (online analytical processing), etc. Dozer deliberately doesn't offer these things, instead focusing on what Pelati calls "precomputed views" using SQL, Python, and JavaScript, and all accessible via low latency. GRPC y REST API.
And it's for this reason, Pelati says, that Dozer can promise better data query latency.
“Because of these design choices, Dozer offers much higher query latency that is necessary for client-facing applications,” Pelati said. “A single developer can activate entire data applications in minutes, which would normally take months of effort. A team doesn't have to build and maintain multiple integrations to save time and money.”
The (not quite) open source factor
While Dozer promotes itself as an "open source" platform, a quick look at its license on GitHub reveals that he uses a Elastic License 2.0 (ELv2), the same license as the Elastic search tool adopted two years ago as part of your transition far of a true open source. In fact, the Elastic license not recognized as open source as it prevents third parties from taking the software and offering it themselves as a hosted or managed service.
More accurately, ELv2 can be called an "available source" license, which effectively means that it offers many of the benefits of a more permissive open source license. like the one at MIT, including codebase transparency, the ability to extend Dozer's capabilities or tune features and fix bugs. This alone is likely enough to win the hearts and minds of companies of all sizes, as long as it's not AWS or some other cloud giant looking to monetize directly on top of Dozer.
However, the company said it intends to switch to a dual license "very soon", where everything in the core Dozer project will be MIT-licensed except for "one core module". Furthermore, the company is quick to emphasize that all of its client libraries are already MIT-licensed, including Python, Dozer-react y JavaScript.
It's worth noting that some companies have created internal tools to solve a problem similar to the one Dozer is tackling, such as Netflix who built solutions with Dozer Several years ago. In particular, one of the main creators behind Bulldozer, Ioannis Papapanagiotou he now works as a consultant to Dozer.
It's still early days for Dozer, but with $3 million in the bank of a large number of high-profile sponsors, the company is pretty well funded as it moves towards commercialization, which will include the introduction of a hosted SaaS version packed with a bunch of extra features. Gudapuri said that he expects this to become operational in the coming months.
“The hosted service will take care of autoscaling, instant deployments, security, compliance, rate limiting, and some additional features,” Gudapur said.
