Cassandra vs Scylla: What are the differences?
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; Scylla: Next Generation Cassandra. Real-time big data database, with scale-up performance of 1,000,000 IOPS per node, scale-out to 100s of nodes and 99 latency of less than 1 msec.
Cassandra and Scylla can be categorized as "Databases" tools.
Cassandra and Scylla are both open source tools. Cassandra with 5.27K GitHub stars and 2.35K forks on GitHub appears to be more popular than Scylla with 5.18K GitHub stars and 615 GitHub forks.
Uber Technologies, Facebook, and Spotify are some of the popular companies that use Cassandra, whereas Scylla is used by Investing.com, Dstillery, and Yieldbot. Cassandra has a broader approval, being mentioned in 342 company stacks & 240 developers stacks; compared to Scylla, which is listed in 11 company stacks and 5 developer stacks.
What is Cassandra?
What is Scylla?
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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.
ScyllaDB provides all of the goodies of Apache Cassandra, including HA, multiDC, replication sharding and so forth. The implementation is in C++ and the internal design is better and thus it achieves 10X the throughput, low 99% latency and more
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