DBMS > EventStoreDB vs. LeanXcale vs. Microsoft Azure Cosmos DB vs. VictoriaMetrics

System Properties Comparison EventStoreDB vs. LeanXcale vs. Microsoft Azure Cosmos DB vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Globally distributed, horizontally scalable, multi-model database service

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Event Store

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

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	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

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

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

www.eventstore.com

www.leanxcale.com

azure.microsoft.com/services/cosmos-db

victoriametrics.com

Technical documentation

developers.eventstore.com

learn.microsoft.com/azure/cosmos-db

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Event Store Limited

LeanXcale

Microsoft

VictoriaMetrics

Initial release

2012

2015

2014

2018

Current release

21.2, February 2021

v1.91, May 2023

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache Version 2.0

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

Server operating systems

Linux
Windows

hosted

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

yes

through Apache Derby

SQL-like query language

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

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

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

C
Java
Scala

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

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

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

Access rights can be defined down to the item level

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