DBMS > BigchainDB vs. Kingbase vs. Riak KV vs. SAP HANA vs. TimesTen

System Properties Comparison BigchainDB vs. Kingbase vs. Riak KV vs. SAP HANA vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Distributed, fault tolerant key-value store

In-memory, column based data store. Available as appliance or cloud service

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Document store

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.44
Rank	#258	Overall
	#117	Relational DBMS

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.bigchaindb.com

www.kingbase.com.cn

www.sap.com/products/hana.html

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.tiot.jp/riak-docs/riak/kv/latest

help.sap.com/hana

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

Developer

BeiJing KINGBASE Information technologies inc.

OpenSource, formerly Basho Technologies

SAP

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

1999

2009

2010

1998

Current release

V8.0, August 2021

3.2.0, December 2022

2.0 SPS07 (April 4, 2023), April 2023

Release 22.1

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Python

C and Java

Erlang

Server operating systems

Linux

Linux
Windows

Linux
OS X

Appliance or cloud-service

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

schema-free

yes

schema-free

yes

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.

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

Standard with numerous extensions

yes

APIs and other access methods

CLI Client
RESTful HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

HTTP API
Native Erlang Interface

JDBC
ODBC

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

user defined functions

Erlang

SQLScript, R

PL/SQL

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

no "single point of failure"

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

selectable replication factor

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

by means of logfiles and checkpoints

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

fine grained access rights according to SQL-standard

yes, using Riak Security

yes

fine grained access rights according to SQL-standard

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