DBMS > Apache Impala vs. Cassandra vs. SWC-DB vs. Titan

System Properties Comparison Apache Impala vs. Cassandra vs. SWC-DB vs. Titan

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Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

Analytic DBMS for Hadoop

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A high performance, scalable Wide Column DBMS

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Wide column store

Graph DBMS

Secondary database models

Document store

Vector DBMS

starting with release V5

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

impala.apache.org

cassandra.apache.org

github.com/kashirin-alex/swc-db
www.swcdb.org

github.com/thinkaurelius/titan

Technical documentation

impala.apache.org/impala-docs.html

cassandra.apache.org/doc/latest

github.com/thinkaurelius/titan/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top level project, originally developped by Facebook

Alex Kashirin

Aurelius, owned by DataStax

Initial release

2013

2008

2020

2012

Current release

4.1.0, June 2022

4.1.3, July 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

Open Source

GPL V3

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

C++

Java

C++

Java

Server operating systems

Linux

BSD
Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like SELECT, DML and DDL statements (CQL)

SQL-like query language

APIs and other access methods

JDBC
ODBC

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

Proprietary protocol
Thrift

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C++

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per object

User authentification and security via Rexster Graph Server

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

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Key customers

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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

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