TileDB
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TileDB | PostHog | |
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12 | 99 | |
1,762 | 17,013 | |
2.1% | 7.2% | |
9.7 | 10.0 | |
5 days ago | 4 days ago | |
C++ | Python | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
TileDB
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Ask HN: Who is hiring? (September 2023)
- single cell genomics: in collaboration with the Chan-Zuckerberg Initiative, we recently released TileDB-SOMA for single cell data, with APIs for both Python and R built around a common storage specification: https://tiledb.com/blog/tiledb-101-single-cell
With TileDB, all data — tables, genomics, images, videos, location, time-series — across multiple domains is captured as multi-dimensional arrays. TileDB Cloud implements a totally serverless infrastructure and delivers access control, easier data and code sharing and distributed computing at global scale, eliminating cluster management, minimizing TCO and promoting scientific collaboration and reproducibility.
Website: https://tiledb.com
GitHub: https://github.com/TileDB-Inc/TileDB
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Why TileDB as a Vector Database
Stavros from TileDB here (Founder and CEO). I thought of requesting some feedback from the community on this blog. It was only natural for a multi-dimensional array database like TileDB to offer vector (i.e., 1D array) search capabilities. But the team managed to do it very well and the results surprised us. We are just getting started in this domain and a lot of new algorithms and features are coming up, but the sooner we get feedback the better.
TileDB-Vector-Search Github repo: https://github.com/TileDB-Inc/TileDB-Vector-Search
TileDB-Embedded (core array engine) Github repo: https://github.com/TileDB-Inc/TileDB
TileDB 101: Vector Search (blog to get kickstarted): https://tiledb.com/blog/tiledb-101-vector-search/
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Ask HN: Who is hiring? (August 2023)
TileDB, Inc. | Full-Time | REMOTE | USA | Greece | https://tiledb.com
TileDB is the database for complex data, allowing data scientists, researchers, and analysts to access, analyze, and share any data with any tool at global scale. We have just launched a vector search library leveraging TileDB and TileDB Cloud for powerful local search and seamless scaling to multi-modal organizational datasets and batched computation: https://tiledb.com/blog/why-tiledb-as-a-vector-database
With TileDB, all data — tables, genomics, images, videos, location, time-series — across multiple domains is captured as multi-dimensional arrays. Our vector search library and other offerings are designed to empower these datasets with extreme interoperability via numerous APIs and tool integrations across the data science ecosystem, eliminating the hassles and inefficiencies of data conversion. TileDB Cloud implements a totally serverless infrastructure and delivers access control, easier data and code sharing and distributed computing at global scale, eliminating cluster management, minimizing TCO and promoting scientific collaboration and reproducibility.
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Ask HN: Who is hiring? (December 2022)
TileDB, Inc. | Full-Time | REMOTE | USA | Greece | https://tiledb.com
TileDB transforms the lives of analytics professionals and data scientists with a universal database, allowing them to access, analyze, and share any data with any tool at global scale. TileDB unifies the way we think about data, delivering superior performance and foundational data management capabilities. All data — tables, genomics, images, videos, location, time-series — across multiple domains is captured as multi-dimensional arrays. TileDB offers extreme interoperability via numerous APIs and tool integrations across the data science ecosystem, eliminating the hassles and inefficiencies of data conversion. TileDB Cloud implements a totally serverless infrastructure and delivers access control, easier data and code sharing and distributed computing at global scale, eliminating cluster management, minimizing TCO and promoting scientific collaboration and reproducibility.
TileDB, Inc. was spun out of MIT and Intel Labs in May 2017 and is backed by Two Bear Capital, Nexus Venture Partners, Uncorrelated Ventures, Intel Capital and Big Pi.
Recent HN article: https://news.ycombinator.com/item?id=23896131
Website: https://tiledb.com
GitHub: https://github.com/TileDB-Inc/TileDB
Docs: https://docs.tiledb.com
Blog: https://tiledb.com/blog
Our headquarters are located in Cambridge, MA and we have a subsidiary in Athens, Greece. We offer the ability to work remotely. If you are located outside of the USA and Greece we have options to accommodate this, don't hesitate to apply!
We have several open positions aimed at increasing TileDB’s feature set, growth and adoption. You will have the opportunity to work on innovative technology that creates impact on challenging and exciting problems in Genomics, Geospatial, Time Series, and more. Immediate features on the roadmap for TileDB Cloud include, advanced distributed computations, advanced computation pushdown, improved multi-cloud deployments and more.
We are actively seeking:
- Senior Golang Engineer
- Senior Python Engineer
- Site Reliability Engineer
- React Frontend Engineer
Apply today at https://tiledb.workable.com !
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Historical weather data API for machine learning, free for non-commercial
Interesting. Have you come across TileDB before?
https://tiledb.com/
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Why isn’t there a decent file format for tabular data?
Hi folks, Stavros from TileDB here. Here are my two cents on tabular data. TileDB (Embedded) is a very serious competitor to Parquet, the only other sane choice IMO when it comes to storing large volumes of tabular data (especially when combined with Arrow). Admittedly, we haven’t been advertising TileDB’s tabular capabilities, but that’s only because we were busy with much more challenging applications, such as genomics (population and single-cell), LiDAR, imaging and other very convoluted (from a data format perspective) domains.
Similar to Parquet:
* TileDB is columnar and comes with a lot of compressors, checksum and encryption filters.
* TileDB is built in C++ with multi-threading and vectorization in mind
* TileDB integrates with Arrow, using zero-copy techniques
* TileDB has numerous optimized APIs (C, C++, C#, Python, R, Java, Go)
* TileDB pushes compute down to storage, similar to what Arrow does
Better than Parquet:
* TileDB is multi-dimensional, allowing rapid multi-column conditions
* TileDB builds versioning and time-traveling into the format (no need for Delta Lake, Iceberg, etc)
* TileDB allows for lock-free parallel writes / parallel reads with ACID properties (no need for Delta Lake, Iceberg, etc)
* TileDB can handle more than tables, for example n-dimensional dense arrays (e.g., for imaging, video, etc)
Useful links:
* Github repo (https://github.com/TileDB-Inc/TileDB)
* TileDB Embedded overview (https://tiledb.com/products/tiledb-embedded/)
* Docs (https://docs.tiledb.com/)
* Webinar on why arrays as a universal data model (https://tiledb.com/blog/why-arrays-as-a-universal-data-model)
Happy to hear everyone’s thoughts.
- Genomics data management reimagined. Analyze and share enormous variant datasets with TileDB Cloud.
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TileDB VS Activeloop hub - a user suggested alternative
2 projects | 20 Oct 2021
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Seeking options for multidimensional data storage
It could be worth checking out TileDB: https://github.com/TileDB-Inc/TileDB The entire system, down to the data format itself, is optimized around storing multi-dimensional arrays. It also supports timestamps and real numbers as dimensions, which could be handy given your example data. [Full disclosure: I currently work for TileDB.]
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Ask HN: Who is hiring? (January 2021)
TileDB, Inc. | Full-Time | REMOTE | USA | Greece | https://tiledb.com
TileDB, Inc. is the company behind TileDB, the first universal data engine. TileDB allows analytics professionals and data scientists to access, analyze, and share complex data sets with any tool at extreme scale. TileDB overcomes the constraints of columnar tables, flat files, and SQL-only tools, handling all data with a multi-dimensional array engine and extreme interoperability across the data science ecosystem. TileDB Cloud is a totally serverless offering of TileDB, which delivers access control and enables distributed computing at planet-scale, eliminating all cluster management and minimizing cost. TileDB, Inc. was spun out of MIT and Intel Labs in May 2017 and closed a $15M Series A in July 2020, following a previous $4M Seed Round.
Recent HN article: https://news.ycombinator.com/item?id=23896131
Website: https://tiledb.com
GitHub: https://github.com/TileDB-Inc/TileDB
Docs: https://docs.tiledb.com
Blog: https://tiledb.com/blog
Our headquarters are located in Cambridge, MA and we have a subsidiary in Athens, Greece. We offer the ability to work remotely, but the candidates must reside either in the US or in Greece. US candidates must be US citizens, whereas Greek candidates must be Greek or EU citizens.
We have several open positions aimed at increasing TileDB’s feature set, growth and adoption. You will have the opportunity to work on innovative technology that creates impact on challenging and exciting problems in Genomics, Geospatial, Time Series, and more. A few features on the roadmap include enhancing our TileDB Cloud offering, optimizing our serverless framework, improving integration with JupyterLab, and expanding our marketplace functionality.
We are primarily seeking:
- Senior Golang Engineer
Apply today at https://tiledb.workable.com !
PostHog
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How Telemetry Saved my Open-Source Platform
It would be a shame not to mention PostHog as the telemetry provider we are using, since it turned out to be extremely useful. Because it is hard to find people who will talk with you about your product, gathering statistics gave us a much greater insight into our users.
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Free tools for developers to build their apps
6- PostHog
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Using Analytics on My Website
Hi HN, PostHog employee here. I'm working on our Web Analytics product, which is currently in beta. It's fun to see us mentioned here :)
I should mention that we have a ton of SDKs (see https://posthog.com/docs/libraries) for back end frameworks and languages, so if you wanted to use PostHog without any client-side JS you could send pageviews and other events manually, but for the vast majority of people it makes more sense to use our JS snippet.
Hijacking this comment to share the roadmap for web analytics https://github.com/PostHog/posthog/issues/18547. It's very much in the launch-early-and-be-embarassed phase, but I would love to hear any feedback or suggestions that people have, particularly if you're already a PostHog user.
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Show HN: Flywheel
how's this different than https://posthog.com/ ?
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Open Source alternatives to tools you Pay for
PostHog - Open Source Alternative to Mixpanel
- Show HN: Monitor your webapp with minimal setup
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Ask HN: Where to Store Logs?
Don't insert the logs/events/analytics into your Application DB. Usually, you send those to specialist datastores (OLAP etc) that process such high volume of data. You can use something like clickhouse [0] for example or use 3rd party SAAS solutions like posthog [1] etc that are built on top of clickhouse
[0] https://clickhouse.com
[1] https://posthog.com
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Ask HN: What would you use to build a mostly CRUD back end today?
I may use Flask-Admin initially to offload the "CRUD" operations to have an initial prototype fast but then drop it ASAP because I don't want to write a "flask-admin application" to fight against later on. If the application is mainly "CRUD", then Flask-Admin is suitable.
Now...
Would you do a breakdown/list of all the jobs you've done by sector/vertical and by function/role and by application functionality?
- [0]: https://flask.palletsprojects.com
- [1]: https://flask-admin.readthedocs.io/en/latest
- [2]: https://flask.palletsprojects.com/en/2.3.x/patterns/celery
- [3]: https://sentry.io
- [4]: https://posthog.com
- [5]: https://www.docker.com
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Ask HN: Who is hiring? (July 2023)
PostHog | Remote (US/Europe timezones) | Full stack engineer, technical ex-founder, tech lead | https://posthog.com
PostHog is the only open-source Product OS, combining product analytics, session recordings, feature flags, cdp and a data warehouse in one.
We have a culture of written async communication (see our handbook [0]), lots of individual responsibility and an opportunity to make a huge impact. Being fully remote means we're able to create a team that is truly diverse. We're based all over the world, and the team includes former YC founders, CTOs turned developers and recent grads.
To apply see https://posthog.com/careers or email us [email protected]
[0] https://posthog.com/handbook/
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planetsin.space -- a PI management and reminder tool
There seems to be posthog.com analytics and AB or feature flag functionality that is blocked by adblockers. Probably that?
What are some alternatives?
ClickHouse - ClickHouse® is a free analytics DBMS for big data
Snowplow - The enterprise-grade behavioral data engine (web, mobile, server-side, webhooks), running cloud-natively on AWS and GCP
RocksDB - A library that provides an embeddable, persistent key-value store for fast storage.
Matomo - Empowering People Ethically with the leading open source alternative to Google Analytics that gives you full control over your data. Matomo lets you easily collect data from websites & apps and visualise this data and extract insights. Privacy is built-in. Liberating Web Analytics. Star us on Github? +1. And we love Pull Requests!
MongoDB C Driver - The Official MongoDB driver for C language
Sentry - Developer-first error tracking and performance monitoring
LevelDB - LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
Plausible Analytics - Simple, open source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics.
libmdbx - One of the fastest embeddable key-value ACID database without WAL. libmdbx surpasses the legendary LMDB in terms of reliability, features and performance.
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
MongoDB Libbson
openreplay - Session replay and analytics tool you can self-host. Ideal for reproducing issues, co-browsing with users and optimizing your product.