DBMS > Bangdb vs. Microsoft Azure Cosmos DB vs. Neo4j vs. Titan

System Properties Comparison Bangdb vs. Microsoft Azure Cosmos DB vs. Neo4j 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

Converged and high performance database for device data, events, time series, document and graph

Globally distributed, horizontally scalable, multi-model database service

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Website

bangdb.com

azure.microsoft.com/services/cosmos-db

neo4j.com

github.com/thinkaurelius/titan

Technical documentation

docs.bangdb.com

learn.microsoft.com/azure/cosmos-db

neo4j.com/docs

github.com/thinkaurelius/titan/wiki

Developer

Sachin Sinha, BangDB

Microsoft

Neo4j, Inc.

Aurelius, owned by DataStax

Initial release

2012

2014

2007

2012

Current release

BangDB 2.0, October 2021

5.19, April 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

GPL version3, commercial licenses 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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C, C++

Java, Scala

Java

Server operating systems

Linux

hosted

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

schema-free and schema-optional

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

All properties auto-indexed by default

yes

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

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

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C#
C++
Java
Python

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

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

Clojure
Java
Python

Server-side scripts

Stored procedures

JavaScript

yes

User defined Procedures and Functions

yes

Triggers

yes, Notifications (with Streaming only)

JavaScript

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

Implicit feature of the cloud service

yes using Neo4j Fabric

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

Implicit feature of the cloud service

Causal Clustering using Raft protocol

available in in Enterprise Version only

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

Tunable consistency, set CAP knob accordingly

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graph

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

Access rights can be defined down to the item level

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

User authentification and security via Rexster Graph Server

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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