Busabase
Busabase is an open-source (MIT) database and workspace for AI agents — data, docs, skills, and apps in one place. Run it locally, self-host it inside your network, or use Busabase Cloud, and turn age
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The open-source data platform you run yourself. Connect and stream data, test and protect it, model it once, and give everyone dashboards, executive briefs and AI answers they can trust.
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Read the full README ↗Tessera puts the whole data workflow in one self-hosted application: connectors and streams, pipelines, data quality, personal-data masking, a catalog, semantic models, dashboards, scheduled reports, executive briefs with forecasts, AI agents and an MCP server. It runs on a laptop, a VM or a container. Your data stays on your hardware, and every feature, including SSO, SCIM and audit, is in the free product under Apache 2.0.
| Bring data in | 25 connector types: PostgreSQL, SQL Server and Fabric Warehouse, Snowflake, BigQuery, Databricks, Redshift, MySQL, Oracle, Trino, ClickHouse, MongoDB, Elasticsearch, Delta Lake, Apache Iceberg, S3, SFTP, REST APIs with OAuth 2, files and any SQLAlchemy database. Ready-made connections to 11 business applications (Salesforce, Dynamics 365, Microsoft 365, HubSpot, Stripe, GitHub, Jira, Zendesk, ServiceNow, Shopify, Airtable), most of them loading only what changed. Copy a whole database in one step, with merge loads detected per table. |
| Mirror it | PostgreSQL mirroring from the database's change log: inserts, updates and deletes arrive within seconds, with no reloads and nothing to install on the database. Schema changes in any source are recorded and announced with their downstream impact. |
| Stream it | Kafka (Confluent, Redpanda, MSK), Azure Event Hubs, Amazon Kinesis, MQTT and HTTP push land continuously in tables. Positions are saved after each batch, so a restart never loses events. Dashboards have a Live mode. |
| Make it trustworthy | Pipelines with dependencies, retries and schedules. Nine kinds of quality rule, suggested from the data, that can stop bad data before it is published. Personal data is detected and masked on publish. Row-level security follows each person everywhere. |
| Define it once | Semantic models hold certified measures such as Revenue and Refund rate, so every report, question and AI answer agrees. A catalog, glossary, lineage and an AI-readiness score per dataset. |
| Use it | Ask questions in plain English, explore 15 visuals, build dashboards by dragging tiles, schedule emailed reports and alerts, share or embed read-only links. |
| Lead with it | One click from any dashboard: where the year will land, how likely each target is, what moved the numbers, with forecasts that state their method and error. |
| Ask AI, safely | Built-in agents (analyst, incident responder, modeler and more) work inside your permissions and every figure they quote is checked against the data. An MCP server gives Claude, IDEs and your own agents the same governed access. |
| Fit in | Power BI, Excel and Tableau read governed data through an OData feed. Pipelines deliver published data to Snowflake, BigQuery, Databricks, Fabric or a Delta lake. OpenLineage to Purview, DataHub or Marquez. dbt docs and tests import. Airflow, Dagster and ADF trigger pipelines over the API. |
Tessera does a lot of what Microsoft Fabric does, in one open-source application you run anywhere. Here is where each is stronger.
| Tessera | Microsoft Fabric | |
|---|---|---|
| Where it runs | Your laptop, server, Kubernetes, AWS or Cloudflare; data stays where you put it | Microsoft's cloud, on Azure capacity |
| Cost | Free (Apache 2.0); you pay only for the machine | Capacity-based subscription |
| What's included | Everything, including SSO, SCIM, audit, row-level security and AI agents | Depends on the capacity and licences you buy |
| Data quality | Built into pipelines: rules suggested from the data, gates that stop bad data before publishing | Through Microsoft Purview or your own notebooks |
| Personal data | Detected and masked on publish, with an AI-readiness score per dataset | Microsoft Purview sensitivity labels and policies, licensed with Microsoft 365 or Purview |
| AI | Agents that work inside your permissions and check every figure, plus an MCP server; bring any model provider | Copilot, on paid Fabric capacity |
| Connectors and mirroring | 25 connector types, 11 business applications, PostgreSQL mirroring | Far more connectors and mirroring sources |
| Scale | One server: comfortable to hundreds of gigabytes | Distributed Spark and warehouse engines for very large data |
| BI | Built-in dashboards, plus Power BI, Excel and Tableau over OData | Power BI, the most mature of the lot |
| Operations | One process you run and upgrade yourself | Fully managed |
Pick Tessera if you want one tool you own, that runs anywhere, with governance and AI built in. Pick Fabric if you need petabyte scale, hundreds of managed connectors and a service Microsoft runs for you. They also work together: Tessera reads from and delivers to Fabric, and Power BI reads Tessera's governed data.
With Docker (Linux, macOS or Windows; amd64 and arm64):
docker run -d --name tessera -p 8710:8710 -v tessera-data:/data ghcr.io/vvipinthomas/tessera:latest
docker logs tessera 2>&1 | grep "Setup code"
Or with Python 3.11 or newer, from the latest release:
pip install "https://github.com/vvipinthomas/tessera/releases/download/v1.7.4/tessera-1.7.4-py3-none-any.whl"
tessera serve
Open http://localhost:8710, enter the setup code, create your admin account and keep Start in demo mode ticked
for a guided tour with sample data. (The tessera package on PyPI is an unrelated project; install from the release
as shown.)
To work from the source code, you need Python 3.11 or newer.
git clone https://github.com/vvipinthomas/tessera.git
cd tessera
python -m venv .venv && source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install -e ".[s3,kafka,mqtt,iceberg,sftp,delta,mongodb]"
tessera serve
This is the beginning of the README. Read the rest at the original. Read the full README ↗