DBMS > EventStoreDB vs. InfinityDB vs. Microsoft Azure Cosmos DB vs. Quasardb vs. STSdb

System Properties Comparison EventStoreDB vs. InfinityDB vs. Microsoft Azure Cosmos DB vs. Quasardb vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

Distributed, high-performance timeseries database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Event Store

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

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

Website

www.eventstore.com

boilerbay.com

azure.microsoft.com/services/cosmos-db

quasar.ai

github.com/STSSoft/STSdb4

Technical documentation

developers.eventstore.com

boilerbay.com/infinitydb/manual

learn.microsoft.com/azure/cosmos-db

doc.quasar.ai/master

Developer

Event Store Limited

Boiler Bay Inc.

Microsoft

quasardb

STS Soft SC

Initial release

2012

2002

2014

2009

2011

Current release

21.2, February 2021

4.0

3.14.1, January 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

Linux
Windows

All OS with a Java VM

hosted

BSD
Linux
OS X
Windows

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

JSON types

yes

integer and binary

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

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

yes

All properties auto-indexed by default

yes

with tags

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API

.NET Client API

Supported programming languages

Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

C#
Java

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

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