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SeekTable (LinkedIn) is an independent Ukrainian product, owned by a private entrepreneur. SeekTable's self-funded approach guarantees its long-term commitment and stability. You can be confident in our ongoing support.
SeekTable, established in 2017, has a time-proven track record of delivering reliable and effective BI solution.
Some clients use SeekTable for many years (5+!) which speaks for itself: SeekTable is designed to be a long-term solution that just works.
Contact us to get more info about SeekTable and the people behind it.
Your data is used only to build visualizations and reports requested by you; see our privacy policy for more details. As any other internet service SeekTable cannot be 100% safe; if you have sensitive data it is highly recommended to use self-hosted (on-prem) SeekTable version.
Vast majority of companies use on-prem SeekTable hosted on their servers. This allows to comply with even rather restrictive data governance policies.
Yes, SeekTable offers free fully-functional personal accounts (all data source connectors are available), and we don't plan to remove them in the future.
With paid subscriptions you can unlock advanced SeekTable features:
Yes! Registered non-profit organizations can apply for a special discount for on-prem SeekTable subscriptions ranging from 50% to 75% off commercial pricing, depending on their business model.
Academic institutions, students can apply for a 100% discount and activate paid SeekTable features for free (except "White label mode") in exchange for a backlink: mention SeekTable in a blog post / sponsor page or somewhere similar.
How to apply? Contact us from your NPO-provided email address.
It is possible to share your cubes and/or reports with your team members using team-sharing feature:
You can easily evaluate this feature with a free 14-day trial: just click "Share to team" and then activate your trial. If you need more time to test team sharing functionality feel free to contact us.
SeekTable's primary purpose is a data exploration/reports generation, and it expects that connected data is already in the form that is suitable for that. Databases (DWs) store well-normalized data and in most cases you can use them as data sources as-is, possibly doing necessary transformations in runtime via SQL; however, CSV files may contain incomplete/raw data that needs cleaning/enrichment or another tranformations. For instance, if your dataset is represented by many CSV files, you might need to combine/join these CSVs before uploading to SeekTable.
You can consider to use these self-service data preparation/transformation tools:
In case of live data sources (database, or auto-refreshed CSV) you might want to automate report generation on schedule (daily, weekly etc) and get a report with newest values directly to your email inbox (or Slack/Drive/Dropbox/OneDrive etc), without the need to open SeekTable app. This is possible in one of the following ways:
In some cases you cannot use SeekTable as a cloud service for number of reasons - say, in the case of sensitive data that should not leave your company's intranet or your local computer (or when your DB is not accesible from the internet at all).
You still can use reporting functionality provided by a
self-hosted SeekTable version which is distributed in the form of docker images.
SeekTable can be installed on any Linux server that is supported by Docker (Kubernetes as well).
It is possible to deploy SeekTable on your local computer too (Linux/MacOS/Windows).
If you're looking for embedded pivot tables as a component take a look to the PivotData microservice
- this is a reporting engine used by SeekTable. It includes
web pivot builder
example that can be integrated into any web application.
Cloud SeekTable UI already supports some non-English languages.
In the case of self-hosted SeekTable deployment, you can customize the app's UI labels, translate
them to your native language, or enable support of multiple languages
(only the languages you need). Ready-to-use translations are available here.
Note that this capability requires activated white-label mode.
Technically UI localization is performed by editing of the JSON configuration (key-value pairs) in the admin area.
Web API is available for the following actions:
This API may be used directly (curl/scripts) or in a code-less way via Zapier/Power Automate.
In some cases you might want to keep reports created by CSV data in sync with:
This kind of automation is possible with Zapier or Microsoft Power Automate. Alternatively, you can write your own shell script and use SeekTable web API directly - say, with curl or your favorite programming language.
If you want to query data files directly (as URLs) this is also possible with DuckDB/MotherDuck connector.
Yes, Parquet files can be queried via DuckDB/MotherDuck connector:
It is very easy to query local parquet files:
SELECT * FROM 'test/*.parquet';
SELECT * FROM read_parquet(['folder1/*.parquet', 'folder2/*.parquet']);
If your Parquet data is accessible as URLs (or hosted in cloud storage like Amazon S3) it can be queried directly:
SELECT * FROM read_parquet('https://filesampleshub.com/download/code/parquet/sample1.parquet');
You can generate and share reports from Google Sheets directly, without need to sync Sheets data with a CSV cube to refresh reports or make your Google Sheets accessible for everyone. For frequently updated data, this ensures you have access to reports that reflect the latest information almost instantly.
To create reports from Google Sheets you can use DuckDB connector with gsheets plugin (note that this approach requires self-hosted SeekTable deployment):
DataSource=:memory:
SELECT * FROM read_gsheet('spreadsheet_url_or_id');
See gsheets plugin documentation for more options - you can specify exact sheet name, cells range etc.
INSTALL gsheets FROM community; LOAD gsheets; CREATE SECRET ( TYPE gsheet, PROVIDER access_token, TOKEN '<your_token>' );See gsheets docs to get instructions about access token generation.
Currently SeekTable supports the following LLM-based functions:
Note that self-hosted SeekTable AI features require either cloud LLM API service (OpenAI, Gemini etc) or self-hosted LLM with OpenAI-compatible API (llama.cpp server, ollama).
If this database is SQL-compatible and it has an ODBC driver for Linux (or ADO.NET provider) we can add it to the list of supported connectors upon request. Examples of databases that may be potentially used with SeekTable:
Most BI tools are read-optimized and do not provide database writeback capability. SeekTable's primary purpose is data exploration, data visualization and reporting so it is also designed for read-only access to the data source.
However sometimes writebacks might be really useful for reports consumers:
At this moment it is possible to have writebacks SeekTable reports only when they are embedded (via iFrame) and this requires some coding on the host app side. Technically this can be implementd via HTML formatting capabilities: generate links inside your reports that 'call' iFrame parent's function to open appropriate record form (that should be fully implemented on your side).
Alternatively, we're working on built-ion seamless writeback capability that can be configured in a no-code way to cover use-cases mentioned above. If you're interested in SeekTable's writebacks please contact us
SeekTable consists of 2 parts:
A self-hosted version is distributed via docker images published on DockerHub; all pre-requisites are already included into these images which makes initial deployment / upgrades really simple.
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