Cassandra vs Google Cloud Datastore: What are the differences?
What is Cassandra? 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.
What is Google Cloud Datastore? A Fully Managed NoSQL Data Storage Service. Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
Cassandra can be classified as a tool in the "Databases" category, while Google Cloud Datastore is grouped under "NoSQL Database as a Service".
"Distributed" is the top reason why over 96 developers like Cassandra, while over 4 developers mention "High scalability" as the leading cause for choosing Google Cloud Datastore.
Cassandra is an open source tool with 5.27K GitHub stars and 2.35K 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 342 company stacks & 240 developers stacks; compared to Google Cloud Datastore, which is listed in 46 company stacks and 16 developer stacks.
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.
This is our primary database, though most of our actual data is stored in static storage. This database houses the metadata necessary for indexing and finding static data.
worked with a client that used datastore as their backend database. helped plan out their schema and architecture. loved the speed and simplicity.
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