DBMS > Amazon Redshift vs. Google Cloud Spanner vs. H2 vs. NuoDB vs. Titan

System Properties Comparison Amazon Redshift vs. Google Cloud Spanner vs. H2 vs. NuoDB vs. Titan

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

Large scale data warehouse service for use with business intelligence tools

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

aws.amazon.com/redshift

cloud.google.com/spanner

www.h2database.com

www.3ds.com/nuodb-distributed-sql-database

github.com/thinkaurelius/titan

Technical documentation

docs.aws.amazon.com/redshift

cloud.google.com/spanner/docs

www.h2database.com/html/main.html

doc.nuodb.com

github.com/thinkaurelius/titan/wiki

Developer

Amazon (based on PostgreSQL)

Google

Thomas Mueller

Dassault Systèmes

originally NuoDB, Inc.

Aurelius, owned by DataStax

Initial release

2012

2017

2005

2013

2012

Current release

2.2.220, July 2023

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

limited edition free

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.

Implementation language

Java

C++

Java

Server operating systems

hosted

All OS with a Java VM

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

JDBC
ODBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python

Java

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

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures and User-Defined Functions

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

data is dynamically stored/cached on the nodes where it is read/written

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Managed transparently by NuoDB

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

Strict serializable isolation

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC

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

Temporary table

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

User authentification and security via Rexster Graph Server

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