DBMS > Cachelot.io vs. H2 vs. YTsaurus

System Properties Comparison Cachelot.io vs. H2 vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Key-value store

Relational DBMS

Document store
Key-value store

Secondary database models

Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.11
Rank	#340	Overall
	#45	Document stores
	#50	Key-value stores

Website

cachelot.io

www.h2database.com

ytsaurus.tech

Technical documentation

www.h2database.com/html/main.html

ytsaurus.tech/docs/en

Developer

Thomas Mueller

Yandex

Initial release

2015

2005

2023

Current release

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Ubuntu

Data scheme

schema-free

yes

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

yes

YQL, an SQL-based language, is supported

APIs and other access methods

Memcached protocol

JDBC
ODBC

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Java

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access Control Lists

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