DBMS > MySQL vs. Sqrrl vs. Titan vs. ToroDB vs. Valentina Server

System Properties Comparison MySQL vs. Sqrrl vs. Titan vs. ToroDB vs. Valentina Server

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines 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.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Widely used open source RDBMS

Adaptable, secure NoSQL built on Apache Accumulo

Titan is a Graph DBMS optimized for distributed clusters.

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Object-relational database and reports server

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.mysql.com

sqrrl.com

github.com/thinkaurelius/titan

github.com/torodb/server

www.valentina-db.net

Technical documentation

dev.mysql.com/doc

github.com/thinkaurelius/titan/wiki

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Amazon

originally Sqrrl Data, Inc.

Aurelius, owned by DataStax

8Kdata

Paradigma Software

Initial release

1995

2012

2016

1999

Current release

8.4.0, April 2024

5.7.5

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache license, version 2.0

Open Source

AGPL-V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Java

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Unix
Windows

All OS with a Java 7 VM

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

yes

with proprietary extensions

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Clojure
Java
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

making use of Hadoop

yes

via pluggable storage backends

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

making use of Hadoop

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Relationships in graph

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

Atomic updates per row, document, or graph entity

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

User authentification and security via Rexster Graph Server

Access rights for users and roles

fine grained access rights according to SQL-standard

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