DBMS > Apache Kylin vs. Geode vs. Riak KV vs. Snowflake

System Properties Comparison Apache Kylin vs. Geode vs. Riak KV vs. Snowflake

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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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Distributed, fault tolerant key-value store

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

Primary database model

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

kylin.apache.org

geode.apache.org

www.snowflake.com

Technical documentation

kylin.apache.org/docs

geode.apache.org/docs

www.tiot.jp/riak-docs/riak/kv/latest

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation, originally contributed from eBay Inc

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2015

2002

2009

2014

Current release

3.1.0, July 2020

1.1, February 2017

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache version 2, commercial enterprise edition

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X

hosted

Data scheme

yes

schema-free

yes

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

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

restricted

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

SQL-like query language (OQL)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Erlang

user defined functions

Triggers

yes

Cache Event Listeners

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

yes, on a single node

ACID

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 per client and object definable

yes, using Riak Security

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

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