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Tinybird<\/a> is not so tiny anymore. The enterprise data startup TechCrunch first covered<\/a> three years ago has been growing at a rapid pace and recently raised a $30 million Series B funding round. According to a source, the company is now valued at $240 million.<\/p>\n Originally from Madrid and now also based in New York, Tinybird is working on a complicated data product with an extremely simple angle. Essentially it helps companies take advantage of the large amounts of data they have so they can reuse this information in their products in near real time.<\/p>\n Tinybird first ingests data in real time from event streaming platforms, such Kafka, Amazon Kinesis or Pub\/Sub. It can also ingest data from BigQuery, Snowflake, Amazon S3 and other storage locations.<\/p>\n After that, developers can filter the data set or combine information from multiple sources using SQL queries. Finally, Tinybird creates API endpoints based on the result of those queries. This way, developers can query their data in their product using a standard JSON-based API. Customers have been using the product for real-time analytics and personalization, sports gambling, smart inventory management and \u2014 more generally \u2014 operational management.<\/p>\n What makes Tinybird particularly interesting is it doesn\u2019t rely on data pipelines \u2014 so-called ETL (Extract\/Transform\/Load) or ELT (Extract\/Load\/Transform) processes \u2014 to connect the data sources with Tinybird. So there\u2019s no need to use Airbyte, Stitch, Fivetran or other data integration tools.<\/p>\n Tinybird is also fast and can ingest a surprisingly large amount of data in little time. \u201cWe have customers that ingest half a million records per second and we process several PetaBytes every day,\u201d co-founder and CEO Jorge G\u00f3mez Sancha told TechCrunch.<\/p>\n The product it built on top of ClickHouse<\/a>, an open-source column-oriented database that is particularly responsive when it comes to processing SQL queries.<\/p>\n \u201cTo enable engineering teams, data teams need a centralized platform to operationalize both batch and streaming data,\u201d G\u00f3mez Sancha said. \u201cThey need a reliable, end-to-end scalable system with fewer technical handoffs, fewer performance compromises, and fewer parts and processes to maintain.\u201d<\/p>\n The company has tripled its revenue in the last year and now works with well-known clients, such as Vercel, Canva and Fanduel. That\u2019s why it raised its Series B round with Balderton leading the round. The company raised a $37M Series A round<\/a> back in 2022 and a $3M seed round<\/a> in 2021.<\/p>\n While Tinybird isn\u2019t raising a ton of money compared to its Series A round, the company said its valuation is \u201csignificantly higher\u201d with the new round. Existing investors CRV, Singular and Crane are also investing again.<\/p>\n \u201cThis round will help us be more aggressive and accelerate the initiatives that will cement our advantages as a real-time data platform for engineering and data teams, from accommodating more data sources and standards like Apache Iceberg that are designed to handle ever growing amounts of data, to using AI to help developers optimize SQL queries and data schemas to reduce latency and increase performance,\u201d G\u00f3mez Sancha added.<\/p>\n It\u2019s certainly true that managing data at scale is not going anywhere. So building a product that makes this process a bit easier sounds like a good business plan.<\/p>\n