Cassandra vs Impala: 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; Impala: Real-time Query for Hadoop. Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.
Cassandra and Impala are primarily classified as "Databases" and "Big Data" tools respectively.
"Distributed" is the primary reason why developers consider Cassandra over the competitors, whereas "Super fast" was stated as the key factor in picking Impala.
Cassandra and Impala are both open source tools. Cassandra with 5.27K GitHub stars and 2.35K forks on GitHub appears to be more popular than Impala with 2.18K GitHub stars and 824 GitHub forks.
According to the StackShare community, Cassandra has a broader approval, being mentioned in 342 company stacks & 240 developers stacks; compared to Impala, which is listed in 15 company stacks and 5 developer stacks.
What is Cassandra?
What is Apache Impala?
Need advice about which tool to choose?Ask the StackShare community!
Sign up to add, upvote and see more prosMake informed product decisions
What are the cons of using Cassandra?
What are the cons of using Apache Impala?
Sign up to get full access to all the companiesMake informed product decisions
Sign up to get full access to all the tool integrationsMake informed product decisions
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