DBMS > Google Cloud Bigtable vs. Graphite vs. IBM Db2 vs. OpenQM vs. SQLite

System Properties Comparison Google Cloud Bigtable vs. Graphite vs. IBM Db2 vs. OpenQM vs. SQLite

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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Common in IBM host environments, 2 different versions for host and Windows/Linux

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

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Multivalue DBMS

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

cloud.google.com/bigtable

github.com/graphite-project/graphite-web

www.ibm.com/products/db2

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

www.sqlite.org

Technical documentation

cloud.google.com/bigtable/docs

graphite.readthedocs.io

www.ibm.com/docs/en/db2

www.sqlite.org/docs.html

Developer

Google

Chris Davis

IBM

Rocket Software, originally Martin Phillips

Dwayne Richard Hipp

Initial release

2015

2006

1983

host version

1993

2000

Current release

12.1, October 2016

3.4-12

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free version is available

Open Source

GPLv2, extended commercial license available

Open Source

Public Domain

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

Python

C and C++

Server operating systems

hosted

Linux
Unix

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

server-less

Data scheme

schema-free

yes

with some exceptions

yes

dynamic column types

Typing

predefined data types such as float or date

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

APIs and other access methods

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

HTTP API
Sockets

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

JavaScript (Node.js)
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
Basic
C
Java
Objective C
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

only with Windows/Unix/Linux Version

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

yes

with separate tools (MQ, InfoSphere)

yes

none

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)

none

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

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

via file-system locks

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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