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Celebrating Dozer v0.1.16 Release and Exiting Stealth Mode

· 6 min read

Dozer is a powerful, plug-and-play data infrastructure back end designed to help developers build real-time,low-latency data APIs (gRPC and REST) from any data source data apps quickly and efficiently. Dozer streamlines the process of accessing and managing real-time data updates. Key features include support for various data types, optimized join indexes structure, high-performance cache and seamless authorization implementation for gRPC/REST methods.

Key Features:

Here is a summary of all key features released till date.

  • Open Source: Dozer has transitioned to a fully open-source model and adopted the Apache 2.0 license. We value the contributions and input from our community.

  • Built with Rust: We care about performance a lot and Dozer is built end to end in Rust

  • Client Libraries: Dozer has libraries in JS, React and Python for easy integration.

  • Reactive SQL Engine : Dozer stays in sync by transforming data in real-time, providing a real time view of your data.

  • Out of the box Data APIs with Protobuf and OpenAPI support: Dozer automatically generates Open API documentation for REST and protobuf definitions for gRPC.

  • Caching Layer: Dozer stores data in an embedded cache and automatically optimses for efficient queries and is horizontally scalable.

  • Wide Variety of Connectors: Dozer connects with databases such as Postgres and MySQL, data warehouses such as Snowflake, data lakes and even the Ethereum ledger.

Here is a short video of Dozer in action.

We were recently featured in TechCrunch with the title "Dozer exits stealth to help any developer build real-time data apps 'in minutes'". The article highlights how Dozer is addressing the challenges of stream data processing, by powering fast, read-only APIs directly from any source via a plug-and-play data infrastructure back end.

Founded by Vivek Gudapuri and Matteo Pelati, Dozer has been in testing with select design partners and has now emerged from stealth for any developer to access. The company also revealed it has raised $3 million in seed funding from Sequoia Capital's Indian arm (via its Surge program), Google's Gradient Ventures, and January Capital.

Dozer's unique approach provides developers with an efficient way to access real-time data updates and APIs within a single product. As a result, developers can save time and money by avoiding the need to build and maintain multiple integrations.

We are extremely proud of our achievements and grateful for the support of our investors and design partners. As we continue to grow, we remain committed to delivering the best possible experience for developers and helping them build real-time data apps quickly and efficiently.

Read the full TechCrunch article here.

Community achievements & other citations:

Exciting News: Dozer is now fully open source!

Based on community feedback, Dozer has transitioned to a fully open-source model and adopted the Apache 2.0 license. We value the contributions and input from our community, and we look forward to continuing to grow and evolve together. Stay tuned for a detailed blog post on this topic in the coming week.

Our Reddit Community:

We are delighted to see the love and support from our community on Reddit. The enthusiasm and engagement from developers and users have been invaluable in shaping the future of Dozer. Check out the Reddit thread here:

Key Enhancements of v0.1.16:

Welcome to this week's update on Dozer! We are excited to announce the release of version v0.1.16, which brings a host of new features and improvements. Alongside this update, we are thrilled to share our recent feature in TechCrunch, announcing that Dozer has exited stealth mode!

1. Fixes and Documentation: We have fixed the README Ubuntu instructions, ensuring a smoother user experience for Ubuntu users. Additionally, we've implemented integration tests on the Github runner, improving the stability and reliability of our codebase.

2. Performance Improvements: Our team has been hard at work optimizing performance, including using MDB_APPEND when possible and reading object store files in parallel. These enhancements contribute to a more efficient and faster user experience.

3. Feature Additions: We have implemented several new features, such as authorization in gRPC methods, support for u128 and i128 Field and FieldType, and snapshotting started messages in the ingestion process. These features will provide more functionality and improve the overall user experience.

4. Code Refactoring and Optimization: Our team has been focusing on optimizing code, including refactoring the Join indexes structure and removing Record::version. This will contribute to a more robust and easier-to-manage codebase.

5. Duration Field and Aggregation Support: We have added Duration, Field & FieldType support, as well as Duration for SQL representation and aggregation support. These additions will provide users with more flexibility when working with time-based data.

6. Bug Fixes: We have addressed several issues, such as fixing minor errors while running with duration, updating resolution atomicity and stream operations, and resolving gRPC errors caused by duration. These bug fixes will contribute to a more stable and reliable product.

Read the full release notes here.

Other Citations and Press Releases:

Join us in celebrating these milestones as we continue to work towards our mission of empowering developers to build real-time data applications with ease and efficiency!

Stay tuned for more updates, and join our community on GitHub, Discord, Twitter, and LinkedIn.


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