DBMS > H2 vs. Kyligence Enterprise vs. RocksDB vs. Snowflake vs. Yaacomo

System Properties Comparison H2 vs. Kyligence Enterprise vs. RocksDB vs. Snowflake vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

A distributed analytics engine for big data, built on top of Apache Kylin

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

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.h2database.com

kyligence.io/kyligence-enterprise

rocksdb.org

www.snowflake.com

yaacomo.com

Technical documentation

www.h2database.com/html/main.html

github.com/facebook/rocksdb/wiki

docs.snowflake.net/manuals/index.html

Developer

Thomas Mueller

Kyligence, Inc.

Facebook, Inc.

Snowflake Computing Inc.

Q2WEB GmbH

Initial release

2005

2016

2013

2014

2009

Current release

2.2.220, July 2023

8.11.4, April 2024

License

Commercial or Open Source

Open Source

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

commercial

Open Source

BSD

commercial

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

All OS with a Java VM

Linux

hosted

Android
Linux
Windows

Data scheme

yes

schema-free

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Java

C
C++
Go
Java
Perl
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

user defined functions

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Source-replica replication

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

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

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

fine grained access rights according to SQL-standard

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