DBMS > BigchainDB vs. GigaSpaces vs. KeyDB vs. MySQL vs. Netezza

System Properties Comparison BigchainDB vs. GigaSpaces vs. KeyDB vs. MySQL vs. Netezza

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Widely used open source RDBMS

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

www.bigchaindb.com

www.gigaspaces.com

github.com/Snapchat/KeyDB
keydb.dev

www.mysql.com

www.ibm.com/products/netezza

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.gigaspaces.com/latest/landing.html

docs.keydb.dev

dev.mysql.com/doc

Developer

Gigaspaces Technologies

EQ Alpha Technology Ltd.

Oracle

since 2010, originally MySQL AB, then Sun

IBM

Initial release

2016

2000

2019

1995

2000

Current release

15.5, September 2020

8.4.0, April 2024

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD-3

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Python

Java, C++, .Net

C++

C and C++

Server operating systems

Linux

Linux
macOS
Solaris
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux

included in appliance

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

yes

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

with proprietary extensions

yes

APIs and other access methods

CLI Client
RESTful HTTP API

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

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC
OLE DB

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C++
Java
Python
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

Lua

yes

proprietary syntax

yes

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

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

Multi-source replication
Source-replica replication

Source-replica replication

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

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept

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