DBMS > BigObject vs. EventStoreDB vs. InfinityDB vs. Riak KV vs. STSdb

System Properties Comparison BigObject vs. EventStoreDB vs. InfinityDB vs. Riak KV vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Industrial-strength, open-source database solution built from the ground up for event sourcing.

A Java embedded Key-Value Store which extends the Java Map interface

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Event Store

Key-value store

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

Key-value store

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

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

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

bigobject.io

www.eventstore.com

boilerbay.com

github.com/STSSoft/STSdb4

Technical documentation

docs.bigobject.io

developers.eventstore.com

boilerbay.com/infinitydb/manual

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

Developer

BigObject, Inc.

Event Store Limited

Boiler Bay Inc.

OpenSource, formerly Basho Technologies

STS Soft SC

Initial release

2015

2012

2002

2009

2011

Current release

21.2, February 2021

4.0

3.2.0, December 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPLv2, commercial license available

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

Java

Erlang

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
Windows

All OS with a Java VM

Linux
OS X

Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

primitive types and user defined types (classes)

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

yes

manual creation possible, using inversions based on multi-value capability

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP API
Native Erlang Interface

.NET Client API

Supported programming languages

Java

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#
Java

Server-side scripts

Stored procedures

Lua

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

manual creation possible, using inversions based on multi-value capability

links between data sets can be stored

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

yes, using Riak Security

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More resources

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provided by Google News

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