DBMS > Apache Kylin vs. Microsoft Azure Synapse Analytics vs. Riak KV vs. Snowflake vs. TDengine

System Properties Comparison Apache Kylin vs. Microsoft Azure Synapse Analytics vs. Riak KV vs. Snowflake vs. TDengine

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Distributed, fault tolerant key-value store

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

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Key-value store

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

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

kylin.apache.org

azure.microsoft.com/services/synapse-analytics

www.snowflake.com

github.com/taosdata/TDengine
tdengine.com

Technical documentation

kylin.apache.org/docs

docs.microsoft.com/azure/synapse-analytics

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

docs.snowflake.net/manuals/index.html

docs.tdengine.com

Developer

Apache Software Foundation, originally contributed from eBay Inc

Microsoft

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

TDEngine, previously Taos Data

Initial release

2015

2016

2009

2014

2019

Current release

3.1.0, July 2020

3.2.0, December 2022

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

AGPL V3, also commercial editions available

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++

Erlang

Server operating systems

Linux

hosted

Linux
OS X

hosted

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

restricted

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

C#
Java
PHP

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

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

Transact SQL

Erlang

user defined functions

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

no "single point of failure"

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

links between data sets can be stored

yes

Transaction concepts

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

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.

User concepts

Access control

yes

yes, using Riak Security

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

yes

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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