DBMS > Amazon CloudSearch vs. Datastax Enterprise vs. Oracle vs. Titan

System Properties Comparison Amazon CloudSearch vs. Datastax Enterprise vs. Oracle 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

A hosted search engine service by Amazon with the data stored in Amazons cloud

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Widely used RDBMS

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.86
Rank	#133	Overall
	#12	Search engines

Score	4.82
Rank	#65	Overall
	#4	Wide column stores

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.datastax.com/products/datastax-enterprise

www.oracle.com/database

github.com/thinkaurelius/titan

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.datastax.com

docs.oracle.com/en/database

github.com/thinkaurelius/titan/wiki

Developer

Amazon

DataStax

Oracle

Aurelius, owned by DataStax

Initial release

2012

2011

1980

2012

Current release

6.8, April 2020

23c, September 2023

License

Commercial or Open Source

commercial

restricted free version is available

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.

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Implementation language

Java

C and C++

Java

Server operating systems

hosted

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

yes

with proprietary extensions

APIs and other access methods

HTTP API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Clojure
Java
Python

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

no "single point of failure"

Sharding, horizontal partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

configurable replication factor, datacenter aware, advanced replication for edge computing

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with 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

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

authentication via encrypted signatures

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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