DBMS > Apache Kylin vs. InterSystems Caché vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. Snowflake

System Properties Comparison Apache Kylin vs. InterSystems Caché vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. Snowflake

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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

A multi-model DBMS and application server

Embeddable relational database for web apps written in pure JavaScript

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

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

Primary database model

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

kylin.apache.org

www.intersystems.com/products/cache

google.github.io/lovefield

azure.microsoft.com/services/synapse-analytics

www.snowflake.com

Technical documentation

kylin.apache.org/docs

docs.intersystems.com

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.microsoft.com/azure/synapse-analytics

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation, originally contributed from eBay Inc

InterSystems

Google

Microsoft

Snowflake Computing Inc.

Initial release

2015

1997

2014

2016

2014

Current release

3.1.0, July 2020

2018.1.4, May 2020

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

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

JavaScript

C++

Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

yes

depending on used data model

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

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C#
C++
Java

JavaScript

C#
Java
PHP

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transact SQL

user defined functions

Triggers

yes

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

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

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

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

Access rights for users, groups and roles

yes

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

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