DBMS > BigObject vs. Postgres-XL vs. Riak KV vs. SWC-DB

System Properties Comparison BigObject vs. Postgres-XL vs. Riak KV vs. SWC-DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Distributed, fault tolerant key-value store

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

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

Wide column store

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

bigobject.io

www.postgres-xl.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.bigobject.io

www.postgres-xl.org/documentation

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

Developer

BigObject, Inc.

OpenSource, formerly Basho Technologies

Alex Kashirin

Initial release

2015

2014

since 2012, originally named StormDB

2009

2020

Current release

10 R1, October 2018

3.2.0, December 2022

0.5, April 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Mozilla public license

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Erlang

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
macOS

Linux
OS X

Linux

Data scheme

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API
Native Erlang Interface

Proprietary protocol
Thrift

Supported programming languages

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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++

Server-side scripts

Stored procedures

Lua

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

links between data sets can be stored

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

yes, using Riak Security

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Basho Revamps Riak Open-Source Database
22 September 2023, InformationWeek

A Critique of Resizable Hash Tables: Riak Core & Random Slicing
26 August 2018, InfoQ.com

Basho to Bolster Riak with DB Plug-Ins
5 May 2014, Datanami

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

Basho launches complete NoSQL software kit - DCD
28 May 2015, DatacenterDynamics

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Share this page