DBMS > Apache Kylin vs. EventStoreDB vs. RocksDB vs. SwayDB

System Properties Comparison Apache Kylin vs. EventStoreDB vs. RocksDB vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Event Store

Key-value store

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

Technical documentation

kylin.apache.org/docs

developers.eventstore.com

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation, originally contributed from eBay Inc

Event Store Limited

Facebook, Inc.

Simer Plaha

Initial release

2015

2012

2013

2018

Current release

3.1.0, July 2020

21.2, February 2021

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C++

Scala

Server operating systems

Linux

Linux
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Foreign keys

Referential integrity

Transaction concepts

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

yes

Atomic execution of operations

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

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