VeloDB

Rockset VS VeloDB Cloud: a comparison of their features and use cases VeloDB is the commercial provider of Apache Doris, a competent open source alternative to Rockset. https://lnkd.in/g6Fn7npi VeloDB Cloud provides cloud-native real-time data analytics services with schemaless support. It is compatible with the MySQL protocol and delivers high data ingestion and querying speed. Start your free trial: https://lnkd.in/gUWMgW73 Or book a call with us for further information: contact@velodb.io #RocksetAlternative #OpenAI #database #analytics #BigData #dataengineering

In the debate between data warehouse and data lake, data warehouse often wins by its high performance, while data lake gains popularity for its openness and ability to store diverse data. At this time of database history, we are facing the convergence of data warehouses and data lakes. Based on its federated query engine and open data lake features, VeloDB has comprehensive data lakehouse capabilities. It can map external data sources, such as Hive, Elasticsearch, and Iceberg, into a data catalog, and automatically update with the source data and cache the external data for high-speed access. VeloDB provides a high-throughput data read and write interface based on the Arrow Flight HTTP data API. It also has an HTTP data API, which allows clients to read data concurrently from multiple backends. Users can quickly access data using Flink Connector, Spark Connector, or the Python SDK (for data science and machine learning).

The BYOC (Bring Your Own Cloud) mode of VeloDB Cloud provides data warehouse services based on open-source Apache Doris. It now supports GCP (Google Cloud Platform) in addition to AWS. Start your free trial now: https://lnkd.in/g7ZJ9vSR

Run VeloDB or Apache Doris on Kubernetes: K8s Operator https://lnkd.in/gVa_gn9E

If you're tired of expensive data lakehouse/analytics solutions and are considering open-source technologies, you definitely would like to read this: Dien, Tran Thanh shares his firsthand experience, proven best practices, and insightful suggestions for migrating from BigQuery to Apache Doris. They are saving $4,500 per month. https://lnkd.in/ggVXgRaB #datalakehouse #BigQuery #dataanalytics #dataengineering #dataplatform #opensource

Comparing Elasticsearch with Apache Doris: Part 2️⃣ #loganalysis #fulltextsearch #aggregation #joinquery #database

Comparing Elasticsearch with Apache Doris: Part 1️⃣ #loganalysis #invertedindex #database

Having trouble with VeloDB? Submit a support ticket so our team can help with it. We're here to help resolve any issues you may have, whether you want to: 👨🔧 Receive technical support 📃 Request a quote 🎁 Tell us about the features you want 🤔 Or simply want to learn more details about VeloDB Simply click into the VeloDB ticketing system: https://lnkd.in/gf6BEVeZ Or email us at contact@velodb.io #database #analytics #snowflake #bigquery #databricks #redshift

Introducing the key features of VeloDB, a modern real-time data warehouse. 🏠 If you'd like to see the complete VeloDB features list and descriptions, feel free to drop a comment below! We're happy to provide more details. #ApacheDoris #datawarehouse #realtimeanalytics #dataengineering

Apache Doris 2.1.4 is available now! 📣 It is optimized in terms of data lakehouse capabilities, query optimizer, and asynchronous materialized view, with higher usability and stability in query execution, semi-structured data analysis, Unique Key model, data ingestion/control, memory management, and privilege management. Just to list a few of the key improvements: 🎈The new query optimizer now supports high-concurrency point queries. 🎈Support native reader of Apache Paimon deletion vector, which largely improves data update/deletion efficiency. 🎈Access controller supports Data Mask with Hive Ranger plugin 🎈Support for transparent rewriting in single-table asynchronous materialized views 🎈Support fetching file lists of Hive/Hudi tables in batches (The list fetching latency for 1.2 million files has reduced from 390s to 46s.)  ... Read more: https://lnkd.in/gr2nAd5F #opensource #database #dataengineer #bigdata #datalakehouse #OLAP #ApacheSoftwareFoundation