Best Relational Database for Apache Kafka

SingleStore (formerly MemSQL), is a distributed, highly-scalable SQL Database that can be run anywhere. With familiar relational models, we deliver the best performance for both transactional and analytical workloads. SingleStore is a scalable SQL database which continuously ingests data to perform operational analysis for your business' front lines. ACID transactions allow you to simultaneously process millions of events per second and analyze billions of rows in relational SQL, JSON geospatial, full-text search, and other formats. SingleStore provides the best data ingestion performance and supports batch loading and real-time data pipelines. SingleStore allows you to query live and historical data with ANSI SQL in a lightning fast manner. You can perform ad-hoc analysis using business intelligence tools, run machine-learning algorithms for real time scoring, and geoanalytic queries in a real time.

Open source solutions that require no maintenance can save you time and money. Your engineers will enjoy working with data because it is integrated, managed and highly reliable. DoubleCloud offers a range of managed open-source services, or you can leverage the full platform's power, including data storage and visualization, orchestration, ELT and real-time visualisation. We offer leading open-source solutions like ClickHouse Kafka and Airflow with deployments on Amazon Web Services and Google Cloud. Our no-code ELT allows real-time data sync between systems. It is fast, serverless and seamlessly integrated into your existing infrastructure. Our managed open-source data visualisation allows you to visualize your data in real time by creating charts and dashboards. Our platform is designed to make engineers' lives easier.

The enterprise database for time series, documents, and vectors. Store any type data and combine the simplicity and scalability NoSQL with SQL. CrateDB is a distributed database that runs queries in milliseconds regardless of the complexity, volume, and velocity.

LeanXcale is fast and scalable database that combines SQL and NoSQL. It can ingest large batches of data and make it available via SQL or GIS for any purpose, including operational applications, analytics and dashboarding. No matter which stack you use, LeanXcale offers both SQL and NoSQL interfaces. The KiVi storage engine can be used as a relational key/value data store. The data can be accessed via the standard SQL API or a direct ACID key/value interface. This key-value interface allows users data ingestion at extremely high rates and efficiently, while avoiding SQL processing overhead. High-scalable, efficient, and distributed storage engine distributed data along a cluster to improve performance and increase reliability.

Apache Druid, an open-source distributed data store, is Apache Druid. Druid's core design blends ideas from data warehouses and timeseries databases to create a high-performance real-time analytics database that can be used for a wide range of purposes. Druid combines key characteristics from each of these systems into its ingestion, storage format, querying, and core architecture. Druid compresses and stores each column separately, so it only needs to read the ones that are needed for a specific query. This allows for fast scans, ranking, groupBys, and groupBys. Druid creates indexes that are inverted for string values to allow for fast search and filter. Connectors out-of-the box for Apache Kafka and HDFS, AWS S3, stream processors, and many more. Druid intelligently divides data based upon time. Time-based queries are much faster than traditional databases. Druid automatically balances servers as you add or remove servers. Fault-tolerant architecture allows for server failures to be avoided.

XTDB, an immutable SQL-based database, is designed to simplify the development of applications and ensure data compliance. It preserves data history automatically, allowing for comprehensive time-travel queries. SQL commands allow users to perform audits and as-of queries. XTDB has been trusted by many companies to transform dynamic applications. It is simple to get started via HTTP, plain SQL or various programming languages. All you need is a client driver, or Curl. Users can easily insert data immutably and query it across time. They can also execute complex joins. Bitemporal modeling is directly beneficial to risk systems. Valid time can be utilized to correlate out-of order trade data while making compliance easy. When things are constantly changing, it can be difficult to expose data across an entire organization. XTDB simplifies the exchange of data and can be used to perform advanced temporal analyses. To model future changes in pricing, tax and discounts, extensive temporal queries are required.