Alternatives
Products that do what ClickHouse-local – a small tool for serverless data analytics does
Me with my friend Vitaly Ludvichenko made an experiment to combine ClickHouse server and client to make a self-contained program running a database engine and processing data without a server: https://github.com/ClickHouse/ClickHouse/pull/150 Development continued in the past 6 years, and now clickhouse-local becomes a swiss-army knife for data processing. Say "ffmpeg" for datasets and more. It can resemble textql, octosql, dsq, duckdb, trdsql, q, datafusion-cli, spyql, but has better capabilities and performance. Here is a tutorial:…
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While building an IoT telemetry solution, we ran into hurdles with Clickhouse. For one, you can't insert quickly AND durably into Clickhouse without setting up something like Kafka, which gets complicated for quick projects wanting to make use of Clickhouse's powerful features. Then, trying to actually query Clickhouse and show data in a UI required a whole backend API to handle auth and permissions. We figured that all these parts together – fast, durable ingest, row-level and column-level security and roles, and realtime streaming – were a lot of scaffolding to have to rebuild for every…
17d ago · wavehouse.dev
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I've built a type-safe semantic layer in code, for ClickHouse. If you're building analytics off ClickHouse in TypeScript, I would love your feedback. With hypequery there is no platform to adopt, no YAML sprawl. It runs where your app runs. Key features: - Define metrics once, reuse them everywhere: Declare dimensions and measures in one place and then pull from the same source of truth. - Compiles to ClickHouse SQL: No service, no proxy, no extra runtime to deploy. It's a library that generates SQL and runs where your app runs. - Multi-tenancy & Authentication ready: Cross-tenant queries…
Jun 2026 · github.com
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Hi HN! We are Ashish and Armend, founders of GlassFlow. Over the last year, we worked with teams running high-throughput pipelines into self-hosted ClickHouse. Mostly for observability and real-time analytics. A question that came repeatedly was: What happens when throughput grows? Usually, things work fine at 10k events/sec, but we started seeing backpressure and errors at >100k. When the throughput per pipeline stops scaling, then adding more CPU/memory doesn’t help because often parts of the pipeline are not parallelized or are bottlenecked by state handling. At this point,…
Apr 2026 · github.com
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I'm building a privacy focused analytics tool, using WebAssembly and DuckDB. You can upload your files (CSV, JSON and Parquet), and interact with them as where they a SQL Server. Your data never leaves your computer, however I do track page views and visitors using Plausible. The next steps are to add forecasting and segmentation, as well as some data visualisation capabilities. I would love to hear your opinion. All code for the repo is available here: https://github.com/dilovancelik/client_side_analytics
2024 · dilovancelik.github.io
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I got tired of the overhead required to run even a simple data analysis - cloud setup, ETL pipelines, orchestration, cost monitoring - so I built a fully local data-stack/IDE where I can write SQL/Py, run it, see results, and iterate quickly and interactively. You get data lake like catalog, zero-ETL, lineage, versioning, and analytics running entirely on your machine. You can import from a database, webpage, CSV, etc. and query in natural language or do your own work in SQL/Pyspark. Connect to local models like Gemma or cloud LLMs like Claude for querying and analysis. You…
Apr 2026 · stream-sock-3f5.notion.site
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Hi HN, there’s a distinct lack of modern self-hosted scale-out query engines. A lot of the innovation in the last 10 years has been in SaaS-only systems. That’s also been true for Firebolt until now. We’re now taking the radical step of offering our query engine as a Docker image that’s free for commercial use without any real restrictions on what you can use it for (basically everything except competing with our SaaS offering). There are helm charts and docker compose files in the repo as well to help you get started. The focus of Firebolt is on low-latency, high-concurrency analytics like…
2025 · github.com
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Hello everyone, While working on other projects, I found myself always having to connect and use SELECT * to see dummy entries or new users. I favored the CLI for monitoring my database entries, especially because I was testing and just adding dummy users + our first normal users in projects. So it became a bit tiring always having to connect to postgres, mysql and give select * queries from the CLI.
2024 · github.com
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I've been building a bunch of random side projects, as I'm sure we all are. Most analytics tools were either too heavy or required juggling multiple free tiers across different subdomains. After looking what's out there I couldn't find a lightweight analytics platform that worked on the free tier of fly.io. It's a single Go binary using DuckDB for events and SQLite for metadata, so there are no external dependencies to manage. Drop a script tag on your site and it auto-captures pageviews and clicks. The part I'm most excited about: it uses an LLM to automatically name raw click events into…
Feb 2026 · github.com
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Hey HN, I'm Karan. I built Logchef because we moved our log workloads to ClickHouse at Zerodha and found the ecosystem lacking for actual log exploration. Tools like Metabase and Grafana are great for dashboards, but log exploration is a different workflow. The Grafana ClickHouse plugin requires manual column configuration for logs, has no field sidebar, and its ad-hoc filters are slow on large tables. Grafana's RBAC is Enterprise-only, and even then it's datasource-level and not at table-level. If someone has access to the ClickHouse datasource, they can query any table. In Logchef, you…
Dec 2025 · logchef.app
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We’ve built SQLRooms, an open-source framework for creating single-node data analytics apps powered by DuckDB. It lets you build fully client-side, data-centric apps using React and DuckDB running in the browser (via WebAssembly) or in Electron. No server or backend is required — apps can work offline, preserve data privacy, and run queries on large datasets with sub-second performance. Features: - Query large datasets in browser with DuckDB (WASM) - Modular design for building composable data UIs (query editors, dashboards, notebooks, etc.) - Data privacy-preserving AI assistant that can…
2025 · sqlrooms.org
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2024 · github.com
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We just launched a small project I'm really proud of — a turbo Database MCP server! https://centralmind.ai - Connect your database to Cursor or Windsurf in just a few clicks. - Chat with PostgreSQL, MSSQL, ClickHouse, Elasticsearch, and more. - Query huge Parquet files instantly with DuckDB in-memory mode. - No downloads, no setup headaches. Short video: https://youtu.be/BboQtxen9tA Built on top of our open-source MCP Database Gateway: https://github.com/centralmind/gateway Note: You’ll need to provide connection strings to your databases. For…
2025 · centralmind.ai
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2024 · github.com
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CH-UI is an open-source web interface for managing and interacting with ClickHouse databases. Key features include an advanced SQL editor with IntelliSense, real-time data visualization, and comprehensive monitoring capabilities. Built with TypeScript and featuring IndexedDB-based caching, it's designed to handle large datasets efficiently. Available as a Docker image for quick deployment.
2025 · github.com
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