DBMS > Galaxybase vs. Google Cloud Bigtable vs. Percona Server for MongoDB vs. TimesTen

System Properties Comparison Galaxybase vs. Google Cloud Bigtable vs. Percona Server for MongoDB vs. TimesTen

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

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

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

In-Memory RDBMS compatible to Oracle

Primary database model

Graph DBMS

Key-value store
Wide column store

Document store

Relational DBMS

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

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

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

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

galaxybase.com

cloud.google.com/bigtable

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

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

Technical documentation

cloud.google.com/bigtable/docs

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

docs.oracle.com/database/timesten-18.1

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

Percona

Oracle, TimesTen Performance Software, HP

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

Initial release

2017

2015

1998

Current release

Nov 20, November 2021

3.4.10-2.10, November 2017

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

GPL Version 2

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 and Java

C++

Server operating systems

Linux

hosted

Linux

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

Data scheme

Strong typed schema

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

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

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

proprietary protocol using JSON

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
Python

C#
C++
Go
Java
JavaScript (Node.js)
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++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined procedures and functions

JavaScript

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

Multi-source replication
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

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

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

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

via In-Memory Engine

yes

User concepts

Access control

Role-based access control

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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