DBMS > Google BigQuery vs. Ignite vs. NuoDB vs. TimesTen

System Properties Comparison Google BigQuery vs. Ignite vs. NuoDB vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

cloud.google.com/bigquery

ignite.apache.org

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

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

Technical documentation

cloud.google.com/bigquery/docs

apacheignite.readme.io/docs

doc.nuodb.com

docs.oracle.com/database/timesten-18.1

Developer

Google

Apache Software Foundation

Dassault Systèmes

originally NuoDB, Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2010

2015

2013

1998

Current release

Apache Ignite 2.6

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

limited edition free

commercial

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

C++, Java, .Net

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes (compute grid and cache interceptors can be used instead)

Java, SQL

PL/SQL

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Managed transparently by NuoDB

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

Temporary table

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Security Hooks for custom implementations

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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