DBMS > Google Cloud Bigtable vs. HyperSQL vs. Infobright vs. Oracle NoSQL vs. PouchDB

System Properties Comparison Google Cloud Bigtable vs. HyperSQL vs. Infobright vs. Oracle NoSQL vs. PouchDB

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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Key-value store
Wide column store

Relational DBMS

Document store
Key-value store
Relational DBMS

Document store

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	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

cloud.google.com/bigtable

hsqldb.org

ignitetech.com/softwarelibrary/infobrightdb

www.oracle.com/database/nosql/technologies/nosql

pouchdb.com

Technical documentation

cloud.google.com/bigtable/docs

hsqldb.org/web/hsqlDocsFrame.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

pouchdb.com/guides

Developer

Google

Ignite Technologies Inc.; formerly InfoBright Inc.

Oracle

Apache Software Foundation

Initial release

2015

2001

2005

2011

2012

Current release

2.7.2, June 2023

23.3, December 2023

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

based on BSD license

commercial

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

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

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

Java

JavaScript

Server operating systems

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Windows

Linux
Solaris SPARC/x86

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

optional

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

Knowledge Grid Technology used instead

yes

via views

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

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

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

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

All languages supporting JDBC/ODBC
Java

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

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

JavaScript

Server-side scripts

Stored procedures

Java, SQL

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

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

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

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

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users and roles

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More resources

DB-Engines blog posts

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