AI · alternatives · 2026
24 alternatives to Strata – an expressive semantic layer that can say no to your LLM
15 minutes from setup to insights, on your own machine. One command starts the server, the CLI connects your warehouse, and your coding agent builds the semantic model.
Strata is a semantic layer that runs locally on your machine to connect data warehouses and generate insights. Users can get started in 15 minutes using a single command to start the server and a CLI to connect their… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.
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Strata▲652One MCP server for AI agents to handle thousands of tools
2025 · klavis.ai · its alternatives →
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Mitzu▲491Ask funnel, retention, and cohort questions in plain language. Mitzu auto-builds a governed semantic layer and answers with deterministic, reviewable SQL.
2024 · mitzu.io · its alternatives →
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Viberia▲146Hey HN, This is my take on the agent harness. Everything on an isometric map. Agents are grouped into "buildings" that run in a sequence or a loop; e.g., the CodeForge has an agent that writes a PRD, another one that implements, and a third that reviews. Everything is customizable, you build your own buildings/teams however you want. It's a Tauri app, really light (about 8x less energy than the closest competitor I benchmarked, so it actually runs from a coffee shop on battery). It's macOS only for now, but ping me if you are willing to test the Windows or Linux version. I've been…
May 2026 · getviberia.com · its alternatives →
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Mantle▲481AI-native cap table management for modern founders
2025 · withmantle.com · its alternatives →
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Metabase▲313Open source business intelligence - Installs in 5 minutes
2015 · metabase.com · its alternatives →
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Baserow▲341Baserow 2.0 introduces workflow automations, the Kuma AI assistant, date dependencies, smarter AI fields, workspace search, and improved security with 2FA.
2022 · baserow.io · its alternatives →
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Layers▲201Marketing agents that know your code for better messaging
Feb 2026 · layers.com · its alternatives →
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Build the semantic layer that makes AI analytics trustworthy
Mar 2026 · metabase.com · its alternatives →
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Context Gateway▲220We built an open-source proxy that sits between coding agents (Claude Code, OpenClaw, etc.) and the LLM, compressing tool outputs before they enter the context window. Demo: https://www.youtube.com/watch?v=-vFZ6MPrwjw#t=9s. Motivation: Agents are terrible at managing context. A single file read or grep can dump thousands of tokens into the window, most of it noise. This isn't just expensive — it actively degrades quality. Long-context benchmarks consistently show steep accuracy drops as context grows (OpenAI's GPT-5.4 eval goes from 97.2% at 32k to 36.6% at 1M…
Mar 2026 · github.com · its alternatives →
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Define metrics once. Use them everywhere.
Jun 2026 · basedash.com · its alternatives →
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Layer▲161Share parts of your spreadsheet, automate your processes
2023 · golayer.io · its alternatives →
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Recipe: Add a semantic layer to SQL; use it drop the requirement for joins/group_by; add in type-checking and a lightweight python-esque import syntax to enable reuse and hierarchical querying. Trilogy is intended to provide an accessible but deep alternative to raw SQL. It offers a new-but-inspired-by-SQL syntax that compiles to various dialects of SQL (with DuckDB as the default). The target audience is people that really like SQL for analytics and data engineering, but want less boilerplate and sharp edges and looser coupling to the DB. Semantic models can be easily shared, composed…
2024 · trilogydata.dev · its alternatives →
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Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024 · its alternatives →
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Deep Work Plan▲114Models matter. Context matters more. Give your agent a plan.
Jun 2026 · deepworkplan.com · its alternatives →
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Hello HN! If you want to connect your agent to a database (say, to build a data analyst chatbot or any kind of agentic app) today you have 2 options: an SQL MCP server or a semantic layer. SQL MCP is the easiest path to setup, especially if you also have a .md knowledge base which the agent can update. It gets quite messy quickly though, especially if there's many interactions or DB is large. Generated SQL is hard to review if you want to understand where the numbers came from, and related queries can be hard to align and compare. The natural alternative is a semantic layer, which is an…
May 2026 · github.com · its alternatives →
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com · its alternatives →
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Connect AI agents to governed metadata via MCP
Jan 2026 · dawiso.com · its alternatives →
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Semantic layer as a service. Your app or your agent sends a structured query spec; 0sql returns one correct, deterministic SQL statement for your warehouse, with row-level security compiled in. It never connects to your warehouse, so your data never leaves your network.
17d ago · 0sql.io · its alternatives →
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After a decade of shipping Django to production, I got tired of solving the same setup problems on every new project. Environment-first settings. Sensible auth defaults. Structured logging. CI from day zero. Pre-commit hooks. Docker. Security hardening. Every project meant two days of boilerplate before writing business logic. So I built Django Keel: a production-ready Django starter that eliminates the yak-shaving. GitHub: https://github.com/CuriousLearner/django-keel *What you get*: - 12-factor config with environment-based secrets - Production-hardened security…
2025 · github.com · its alternatives →
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Hi HN, Working with multiple projects, I got tired of re-explaining our complex multi-node system to LLMs. Documentation helped, but plain text is hard to search without indexing and doesn't work across projects. I built Linggen to solve this. My Workflow: I use the Linggen VS Code extension to "init my day." It calls the Linggen MCP to load memory instantly. Linggen indexes all my docs like it’s remembering them—it is awesome. One click loads the full architectural context, removing the "cold start" problem. The Tech: Local-First: Rust + LanceDB. Code and embeddings stay on your machine. No…
Dec 2025 · github.com · its alternatives →
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It’s written in Python and I call it GoalChain. It lets you build a conversation flow graph that the user traverses. When there’s enough input it spits out a dictionary with the defined fields. Otherwise it will jump state to state as led by the user. It was fun to write, and it’s surprisingly effective if you keep in mind you’re prompt-engineering every string and field name. README.md has a mini-tutorial. Would be cool to get some ideas for how to build it further and what improvements I could make.
2024 · github.com · its alternatives →
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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 · its alternatives →
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
2025 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →