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Key Differences Between Apache Ignite, Hazelcast, Cassandra, and Tarantool

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Key Differences Between Apache Ignite, Hazelcast, Cassandra, and Tarantool

The main difference of Apache Ignite from the others is the number of functionalities and simplicity of use.

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Apache Ignite is widely used around the world and is growing all the time. Companies like Barclays, Misys, Sberbank (3rd largest banks 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 other 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 IgniteHazelcast, 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 reading/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 notice 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.

The Apache Ignite bookPortions of this article were taken from the book The Apache Ignite book. If it got you interested, check out the rest of the book for more helpful information. There is a special 20% discount for the DZone readers, please use the following coupon.

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 reading/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. 

I strongly guess the above comparison between different database will save your times during the times of choosing the right product. For more details and advanced topics about Apache Ignite, please check the sample chapter of  The Apache Ignite book.

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Topics:
apache ignite ,gridgain ,hazelcase ,apache cassandra ,tarantool ,in-memory caching ,in-memory data grid ,database ,key differences between databases

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