{"id":112227,"date":"2025-10-09T23:43:07","date_gmt":"2025-10-09T23:43:07","guid":{"rendered":"https:\/\/www.europesays.com\/ie\/112227\/"},"modified":"2025-10-09T23:43:07","modified_gmt":"2025-10-09T23:43:07","slug":"tigris-data-raises-25m-for-its-ai-optimized-cloud-storage-service","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ie\/112227\/","title":{"rendered":"Tigris Data raises $25M for its AI-optimized cloud storage service"},"content":{"rendered":"

Tigris Data Inc., the operator of an object storage service optimized for artificial intelligence workloads, has raised $25 million in early-stage funding.<\/p>\n

The company said<\/a> in its announcement of the Series A round today that Spark Capital was the lead investor. Returning backer Andreessen Horowitz chipped in as well.<\/p>\n

Sunnyvale, California-based Tigris positions its service\u00a0 as an alternative to the major public clouds\u2019 object storage offerings. The service is S3-compatible, which means that it can be used by applications originally written for Amazon S3 without major code modifications. That lowers the entry barrier for new customers.<\/p>\n

Tigris says that its platform is particularly suitable for storing small files such as embeddings, the mathematical structures in which AI models keep data. It claims that the platform can make such files available to workloads with less latency than S3. Reducing data retrieval times enables AI applications to process prompts faster.<\/p>\n

One way Tigris reduces latency is by caching frequently used files. The company\u2019s cache is based on a data structure known as a log-structured merge-tree, or LSM for short. An LSM boosts performance by optimizing how information is organized in storage.\u00a0<\/p>\n

A data storage device is divided into numerous segments that each hold a tiny amount of information. Usually, applications can read data from adjacent segments significantly faster than from non-adjacent ones. The LMS data structure used by Tigris keeps information in adjacent segments to speed up retrieval times.<\/p>\n

The company\u2019s platform also reduces latency in other ways. If Tigris detects that a data repository is frequently accessed by users in a certain region, it can move the repository to that region or create a cached copy. That reduces the distance that users\u2019 network traffic must travel and thereby speeds up access times.<\/p>\n

Tigris\u2019 platform offers four storage infrastructure tiers. There\u2019s a standard tier, another that is geared toward infrequently accessed files and two optimized for archived datasets. The latter tiers trade off some speed for lower pricing.<\/p>\n

Developers can move their workloads\u2019 data to Tigris from other platforms using a feature called Tigris shadow buckets. The feature gradually copies an application\u2019s most frequently used records. That removes the need to move the entire datasets at once, which is an often complicated endeavor with the potential to cause technical issues.<\/p>\n

TechCrunch reported<\/a>\u00a0today that Tigris has more than 4,000 customers. The company uses data centers in Virginia, Chicago and San Jose to host those customers\u2019 files. Tigris will use its new funding to roll out its hardware to additional data centers in London, Frankfurt and Singapore.<\/p>\n

Photo of Tigris Data\u2019s founders: Tigris Data<\/p>\n

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