DBMS > Google Cloud Bigtable vs. OpenQM vs. Percona Server for MongoDB vs. Transbase

System Properties Comparison Google Cloud Bigtable vs. OpenQM vs. Percona Server for MongoDB vs. Transbase

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

QpenQM is a high-performance, self-tuning, multi-value DBMS

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store
Wide column store

Multivalue DBMS

Document store

Relational DBMS

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

cloud.google.com/bigtable

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.percona.com/mongodb/software/percona-server-for-mongodb

www.transaction.de/en/products/transbase.html

Technical documentation

cloud.google.com/bigtable/docs

docs.percona.com/percona-distribution-for-mongodb

www.transaction.de/en/products/transbase/features.html

Developer

Google

Rocket Software, originally Martin Phillips

Percona

Transaction Software GmbH

Initial release

2015

1993

2015

1987

Current release

3.4-12

3.4.10-2.10, November 2017

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

GPL Version 2

commercial

free development license

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++

C and C++

Server operating systems

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

proprietary protocol using JSON

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net
Basic
C
Java
Objective C
PHP
Python

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

yes

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

via In-Memory Engine

User concepts

Access control

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

Access rights can be defined down to the item level

Access rights for users and roles

fine grained access rights according to SQL-standard

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

Google Launches Cloud Bigtable, A Highly Scalable And Performant NoSQL Database
6 May 2015, TechCrunch

Now anyone can use the database behind Google's most popular products
6 May 2015, Fortune

provided by Google News

There are lots of ways to put a database in the cloud – here's what to consider
15 September 2023, The Register

FerretDB goes GA: Gives you MongoDB, without the MongoDB...
15 May 2023, The Stack

The essential guide to MongoDB security
2 February 2017, InfoWorld

The Case Against the Server Side Public License (SSPL)
11 October 2022, The New Stack

Supercharge your Amazon RDS for MySQL deployment with ProxySQL and Percona Monitoring and Management ...
12 October 2018, AWS Blog

provided by Google News

Share this page