Azure Cosmos DB vs Cassandra: What are the differences?
Developers describe Azure Cosmos DB as "A fully-managed, globally distributed NoSQL database service". Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development. On the other hand, Cassandra is detailed as "A partitioned row store. Rows are organized into tables with a required primary key". Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Azure Cosmos DB can be classified as a tool in the "NoSQL Database as a Service" category, while Cassandra is grouped under "Databases".
"Best-of-breed NoSQL features" is the top reason why over 13 developers like Azure Cosmos DB, while over 96 developers mention "Distributed" as the leading cause for choosing Cassandra.
Cassandra is an open source tool with 5.23K GitHub stars and 2.33K GitHub forks. Here's a link to Cassandra's open source repository on GitHub.
According to the StackShare community, Cassandra has a broader approval, being mentioned in 337 company stacks & 230 developers stacks; compared to Azure Cosmos DB, which is listed in 24 company stacks and 23 developer stacks.
What is Azure Cosmos DB?
What is Cassandra?
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Stitch is a wrapper around a Cassandra database. It has a web application that provides read-access to the counts through an HTTP API. The counts are written to Cassandra in two distinct ways, and it's possible to use either or both of them:
Real-time: For real-time updates, Stitch has a processor application that handles a stream of events coming from a broker and increments the appropriate counts in Cassandra.
Batch: The batch part is a MapReduce job running on Hadoop that reads event logs, calculates the overall totals, and bulk loads this into Cassandra.
Cassandra is our data management workhorse. It handles all our key-value services, supports time-series data storage and retrieval, securely stores all our audit trails, and backs our Datomic database.
While we experimented with Cassandra in the past, we are no longer using it. It is, however, open for consideration in future projects.
We are using Cassandra in a few of our apps. One of them is as a count service application to track the number of shares, clicks.. etc