DBMS > Microsoft Azure Cosmos DB vs. Oracle Berkeley DB vs. Titan vs. Ultipa

System Properties Comparison Microsoft Azure Cosmos DB vs. Oracle Berkeley DB vs. Titan vs. Ultipa

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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

Globally distributed, horizontally scalable, multi-model database service

Widely used in-process key-value store

Titan is a Graph DBMS optimized for distributed clusters.

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	0.11
Rank	#338	Overall
	#32	Graph DBMS

Website

azure.microsoft.com/services/cosmos-db

www.oracle.com/database/technologies/related/berkeleydb.html

github.com/thinkaurelius/titan

www.ultipa.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/cd/E17076_05/html/index.html

github.com/thinkaurelius/titan/wiki

www.ultipa.com/document

Developer

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Aurelius, owned by DataStax

Ultipa

Initial release

2014

1994

2012

2019

Current release

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Apache license, version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, Java, C++ (depending on the Berkeley DB edition)

Java

Server operating systems

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

only with the Berkeley DB XML edition

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Clojure
Java
Python

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

JavaScript

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Multi-item ACID transactions with snapshot isolation within a partition

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

User concepts

Access control

Access rights can be defined down to the item level

User authentification and security via Rexster Graph Server

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