DBMS > BigchainDB vs. GigaSpaces vs. MaxDB vs. PouchDB vs. RocksDB

System Properties Comparison BigchainDB vs. GigaSpaces vs. MaxDB vs. PouchDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A robust and reliable RDBMS optimized to run all major SAP solutions

JavaScript DBMS with an API inspired by CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Document store

Key-value store

Secondary database models

Graph DBMS
Search engine

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.gigaspaces.com/latest/landing.html

maxdb.sap.com/documentation

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

Developer

Gigaspaces Technologies

SAP, acquired from Software AG (Adabas-D) in 1997

Apache Software Foundation

Facebook, Inc.

Initial release

2016

2000

1984

2012

2013

Current release

15.5, September 2020

7.9.10.12, February 2024

7.1.1, June 2019

9.2.1, May 2024

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache Version 2; Commercial licenses available

commercial

Limited community edition free

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

Java, C++, .Net

C++

JavaScript

C++

Server operating systems

Linux

Linux
macOS
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

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

Linux

Data scheme

schema-free

yes

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

via views

SQL

Support of SQL

SQL-99 for query and DML statements

yes

APIs and other access methods

CLI Client
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
WebDAV

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C++
Java
Python
Scala

.Net
C#
Java
Perl
PHP
Python

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

yes

Role-based access control

fine grained access rights according to SQL-standard

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