Database technology provider MongoDB today announced MongoDB Atlas, an elastic, on-demand cloud service that includes infrastructure and turnkey management.
Separately, the company also announced a new MongoDB Connector for Apache Spark, now generally available and ready for production usage.
Citing feedback from a recent survey of more than 2,000 members of the MongoDB community the company says that 30% of respondents deploy on more than one public cloud. MongoDB Atlas will enable multi-vendor cloud strategies. To accommodate that use, the company says Atlas will be available on all popular cloud platforms - initially on Amazon Web Services, followed by Microsoft Azure, and then Google Cloud Platform.
According to MongoDB, Atlas will be operated by the experts who design and engineer the database, meaning that developers no longer need to worry about operational tasks such as provisioning, configuration, patching, upgrades, backups, and failure recovery. In addition, the new DBaaS offers elastic scalability, either by scaling up on a range of instance sizes or scaling out with automatic sharding, all with no application downtime.
Describing the new offering as a “major milestone,” Dev Ittycheria, president and CEO of MongoDB, said that Atlas takes everything the company knows about operating MongoDB and packages it into a convenient, secure, elastic, on-demand service. By running on MongoDB Atlas, added Eliot Horowitz, CTO and co-founder of MongoDB, developers can trust that their applications will be available, secure, scale, and also that they will be able to avoid the downtime that comes from applying patch updates.
MongoDB says Atlas delivers high availability with an architecture that is fault-tolerant and self-healing. Recovery from instance failures is transparent and fully automated. MongoDB Atlas automatically and continuously monitors and backs up customer databases, providing always-on availability and granular point-in-time recovery at the click of a button. A minimum of three copies of user data is replicated across availability zones and continuously backed up.
In addition, it says that the service delivers high throughput and low latency for read and write operations to the most demanding workloads at virtually any s cale. This consistent, predictable performance eliminates the need for separate caching tiers, and can deliver 80% cost reduction compared to traditional enterprise database software. Atlas provides multiple levels of security, enabled by default, including access control, network isolation using Amazon VPC, IP whitelists, and end-to-end encryption of all data.
MongoDB says it has worked with Databricks, the company founded by the team that created the Apache Spark project, and the new MongoDB connector for Spark has achieved Databricks Certified Application status for Spark, so that developers can be assured that the connector provides seamless integration and complete API compatibility between Spark processes and MongoDB.
The documentation for MongoDB Atlas is available here.