DBMS > Google BigQuery vs. Infobright vs. Riak TS vs. STSdb

System Properties Comparison Google BigQuery vs. Infobright vs. Riak TS vs. STSdb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

cloud.google.com/bigquery

ignitetech.com/softwarelibrary/infobrightdb

github.com/STSSoft/STSdb4

Technical documentation

cloud.google.com/bigquery/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Google

Ignite Technologies Inc.; formerly InfoBright Inc.

Open Source, formerly Basho Technologies

STS Soft SC

Initial release

2010

2005

2015

2011

Current release

3.0.0, September 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPLv2, commercial license available

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

Erlang

Server operating systems

hosted

Linux
Windows

Linux
OS X

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Knowledge Grid Technology used instead

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

.NET Client API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

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

exploiting MySQL or PostgreSQL frontend capabilities

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.