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Key differences between Apache Ignite, Hazelcast, Cassandra and Tarantool

Apache Ignite is widely used around the world and is growing all the time. Companies like Barclays, Misys, Sberbank (3r largest bank in Europe), ING, JacTravel all use Ignite to power pieces of their architecture that are critical to the day-to-day operations of those organizations. Moreover, the vendor like TIBCO uses core caching data-grid module of Apache Ignite with advanced indexing and SQL capability for their Master Data Management platform.

However there are a few others alternatives to Apache Ignite from other vendors such as HazelCast, Oracle, Ehcache, GemFire, etc. The main difference of Apache Ignite from the others is the number of functionalities and simplicity of use. Apache Ignite provides a variety of functionalities, which you can use for different use cases. The key differences between the Apache Ignite, Hazelcast, and Apache Cassandra are as follows:


Feature Apache Ignite Hazelcast Apache Cassandra
Data model Key-value Key-value Column family
Durability Yes (WAL and,memory pages) Yes (not free) Yes (commit log and,SStable)
SQL support Yes SQL like query
language		 No, support SQL like
query language
Secondary index Yes Yes Yes
Big data accelerator Yes Yes (not free) No
Transaction Yes Yes CAS – not ACID
compliant
Use case Most suitable for
read/write-heavy workloads		 Most suitable
for read/write-heavy workloads		 Most suitable for
write-heavy
workloads
Server-side scripting Yes (compute &
service grid)		 Yes No
Availability High High High
Streaming Yes Yes (not free) No
In-memory
Map/Reduce		 Yes Yes No

From the above table, you can see that unlike other competitors, Apache Ignite provides durable memory architecture (free of charges), server-side scripting (compute grid), a set of components called In-memory Hadoop accelerator and Spark shared RDD that can deliver real-time performance to Hadoop and Spark users. The Apache Ignite is the right choice when you need scalability and high availability with the capability of processing high volume transactions. It is the perfect platform for the mission-critical data on commodity hardware or cloud infrastructure.

Now, let’s compare the Apache Ignite functionalities with another in-memory database named Tarantool. Tarantool is an in-memory database, design by a team led by a former MySQL engineer.


Feature Apache Ignite Tarantool
Data model Key-value Container like
Durability Yes (WAL and memory pages) Yes (WAL, LSM tree)
SQL support Yes No
Secondary index Yes Yes
Big data accelerator Yes No
ORM support Yes No
Distributed transaction Yes No
Use case Most suitable for
read/write-heavy workloads		 Most suitable
for read/write-heavy workloads
Server-side scripting Yes (compute &
service grid)		 Yes (using programming
language Lua)
Availability High High! Master-slave replication
Streaming Yes Yes (built-in queues)
In-memory
Map/Reduce		 Yes Yes

If you carefully study the above table, you can notice that Tarantool doesn’t support SQL and distributed transactions. Even Tarantool doesn’t provide any ORM support for using Hibernate or MyBatis. From the architecture point of view, Tarantool uses Master-Slave replication, which can proceed data loss whenever a master fails.
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