DBMS > Google BigQuery vs. Newts vs. SQL.JS vs. TimesTen

System Properties Comparison Google BigQuery vs. Newts vs. SQL.JS vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Time Series DBMS based on Cassandra

Port of SQLite to JavaScript

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

cloud.google.com/bigquery

opennms.github.io/newts

sql.js.org

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

Technical documentation

cloud.google.com/bigquery/docs

github.com/OpenNMS/newts/wiki

sql.js.org/documentation/index.html

docs.oracle.com/database/timesten-18.1

Developer

Google

OpenNMS Group

Alon Zakai

enhancements implemented by others

Oracle, TimesTen Performance Software, HP

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

Initial release

2010

2014

2012

1998

Current release

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

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

Java

JavaScript

Server operating systems

hosted

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

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

Data scheme

yes

schema-free

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

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP REST
Java API

JavaScript API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

JavaScript

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

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

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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