DBMS > Google Cloud Bigtable vs. IBM Cloudant vs. Immudb vs. JaguarDB vs. SQLite

System Properties Comparison Google Cloud Bigtable vs. IBM Cloudant vs. Immudb vs. JaguarDB 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.

Database as a Service offering based on Apache CouchDB

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Performant, highly scalable DBMS for AI and IoT applications

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store
Wide column store

Document store

Key-value store

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	0.24
Rank	#295	Overall
	#42	Key-value stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

cloud.google.com/bigtable

www.ibm.com/products/cloudant

github.com/codenotary/immudb
immudb.io

www.jaguardb.com

www.sqlite.org

Technical documentation

cloud.google.com/bigtable/docs

cloud.ibm.com/docs/Cloudant

docs.immudb.io

www.jaguardb.com/support.html

www.sqlite.org/docs.html

Developer

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Codenotary

DataJaguar, Inc.

Dwayne Richard Hipp

Initial release

2015

2010

2020

2015

2000

Current release

1.2.3, April 2022

3.3 July 2023

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL V3.0

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

Erlang

C++

the server part. Clients available in other languages

Server operating systems

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like syntax

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

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

RESTful HTTP/JSON API

gRPC protocol
PostgreSQL wire protocol

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

View functions (Map-Reduce) in JavaScript

Triggers

yes

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

Multi-source replication
Source-replica replication

Multi-source replication

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)

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic 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)

Access rights for users can be defined per database

rights management via user accounts

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