DBMS > AgensGraph vs. IBM Db2 Event Store vs. Riak KV vs. Snowflake vs. STSdb

System Properties Comparison AgensGraph vs. IBM Db2 Event Store vs. Riak KV vs. Snowflake vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Distributed Event Store optimized for Internet of Things use cases

Distributed, fault tolerant key-value store

Cloud-based data warehousing service for structured and semi-structured data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Graph DBMS
Relational DBMS

Event Store
Time Series DBMS

Key-value store

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

Relational DBMS

Key-value store

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

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

bitnine.net/agensgraph

www.ibm.com/products/db2-event-store

www.snowflake.com

github.com/STSSoft/STSdb4

Technical documentation

bitnine.net/documentation

www.ibm.com/docs/en/db2-event-store

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

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

IBM

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

STS Soft SC

Initial release

2016

2017

2009

2014

2011

Current release

2.1, December 2018

2.0

3.2.0, December 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free developer edition available

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Erlang

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X

hosted

Windows

Data scheme

depending on used data model

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

.NET Client API

Supported programming languages

C
Java
JavaScript
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

yes

Erlang

user defined functions

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

no "single point of failure"

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Active-active shard replication

selectable replication factor

yes

none

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

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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