DBMS > AnzoGraph DB vs. CockroachDB vs. Microsoft SQL Server vs. Titan

System Properties Comparison AnzoGraph DB vs. CockroachDB vs. Microsoft SQL Server 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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Microsofts flagship relational DBMS

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Graph DBMS
RDF store

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.cockroachlabs.com

www.microsoft.com/en-us/sql-server

github.com/thinkaurelius/titan

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

www.cockroachlabs.com/docs

learn.microsoft.com/en-US/sql/sql-server

github.com/thinkaurelius/titan/wiki

Developer

Cambridge Semantics

Cockroach Labs

Microsoft

Aurelius, owned by DataStax

Initial release

2018

2015

1989

2012

Current release

2.3, January 2021

24.1.0, May 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0, commercial license available

commercial

restricted free version is available

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

Server operating systems

Linux

Linux
macOS
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

dynamic schema

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

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C++
Java
Python

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication using RAFT

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

User concepts

Access control

Access rights for users and roles

Role-based access control

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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