Best Database as a Service (DBaaS) Providers for Amazon Redshift

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

Amazon Relational Database Service (Amazon RDS), makes it easy to create, manage, and scale a cloud-based relational database. It offers a cost-efficient, resizable storage capacity and automates time-consuming admin tasks like database setup, patching, backups, and hardware provisioning. It allows you to concentrate on your applications, so they can provide the high performance, security, compatibility, and high availability that they require. Amazon RDS can be used on several database instance types, optimized for memory, performance, or I/O. It offers six familiar database engines to choose, including PostgreSQL and MySQL, MariaDB, Oracle Database and SQL Server. To easily replicate or migrate your existing databases to Amazon RDS, you can use the AWS Database Migration Service.

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is five times faster that standard MySQL databases and three time faster than standard PostgreSQL database. It offers the same security, availability, reliability, and cost-effectiveness as commercial databases, but at a fraction of the cost. Amazon Aurora is fully managed and maintained by Amazon Relational Database Service, (RDS). This automates tedious administration tasks such as hardware provisioning, database setup, patching and backups. Amazon Aurora is a distributed, fault-tolerant and self-healing storage that auto-scales up 64TB per database instance. It offers high availability and performance with up to 15 low latency read replicas, point in time recovery, continuous backup to Amazon S3, replication across threeAvailability Zones, and continuous backup to Amazon S3.

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Stop wasting your time maintaining and provisioning databases yourself. Create isolated test databases quickly to deliver features faster. Equip your developers to stay on track with fast-paced projects by providing them with ready-to-go databases. As part of your CI/CD process, you can create pre-populated databases to test with and then automatically remove them once the tests are complete. With built-in container orchestration, quickly and easily spin up databases with the click of a single button for testing, bug replication, demos and more. Our patented subsetter shrinks PBs to GBs, without compromising referential integrity. Then, Tonic Ephemeral is used to create a database that contains only the data required for development. This will reduce cloud costs and maximize efficiency. Tonic Ephemeral and our patented subsetter can be used together to get the data subsets that you need, for as long as you require them. Get your developers to access one-off datasets that are only needed for local development.