DBMS > BigchainDB vs. Riak KV vs. SQLite vs. TimesTen vs. Transwarp Hippo

System Properties Comparison BigchainDB vs. Riak KV vs. SQLite vs. TimesTen vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

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

Distributed, fault tolerant key-value store

Widely used embeddable, in-process RDBMS

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.

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Document store

Key-value store

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

Relational DBMS

Vector DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

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

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

www.bigchaindb.com

www.sqlite.org

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

www.transwarp.cn/en/subproduct/hippo

Technical documentation

bigchaindb.readthedocs.io/en/latest

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

www.sqlite.org/docs.html

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

Developer

OpenSource, formerly Basho Technologies

Dwayne Richard Hipp

Oracle

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

Initial release

2016

2009

2000

1998

2023

Current release

3.2.0, December 2022

3.46.1 (13 August 2024), August 2024

Release 22.1

1.0, May 2023

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache version 2, commercial enterprise edition

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

Erlang

C++

Server operating systems

Linux

Linux
OS X

server-less

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

Linux
macOS

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes

Vector, Numeric and String

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

restricted

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

APIs and other access methods

CLI Client
RESTful HTTP API

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

RESTful HTTP API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

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

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

C++
Java
Python

Server-side scripts

Stored procedures

Erlang

PL/SQL

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

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

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

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

via file-system locks

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

by means of logfiles and checkpoints

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

yes, using Riak Security

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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