DBMS > Amazon Redshift vs. Elasticsearch vs. FatDB vs. Titan

System Properties Comparison Amazon Redshift vs. Elasticsearch vs. FatDB vs. Titan

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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

Large scale data warehouse service for use with business intelligence tools

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Search engine

Document store
Key-value store

Graph DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Website

aws.amazon.com/redshift

www.elastic.co/elasticsearch

github.com/thinkaurelius/titan

Technical documentation

docs.aws.amazon.com/redshift

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

github.com/thinkaurelius/titan/wiki

Developer

Amazon (based on PostgreSQL)

Elastic

FatCloud

Aurelius, owned by DataStax

Initial release

2012

2010

2012

Current release

8.6, January 2023

License

Commercial or Open Source

commercial

Open Source

Elastic License

commercial

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

hosted

All OS with a Java VM

Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

restricted

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

Via inetgration in SQL Server

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

via applications

yes

Triggers

yes

by using the 'percolation' feature

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graph

Transaction concepts

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

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.

yes

Memcached and Redis integration

User concepts

Access control

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

User authentification and security via Rexster Graph Server

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