DBMS > Apache Kylin vs. Geode vs. InfinityDB vs. Microsoft SQL Server

System Properties Comparison Apache Kylin vs. Geode vs. InfinityDB vs. Microsoft SQL Server

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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

A Java embedded Key-Value Store which extends the Java Map interface

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

kylin.apache.org

geode.apache.org

boilerbay.com

www.microsoft.com/en-us/sql-server

Technical documentation

kylin.apache.org/docs

geode.apache.org/docs

boilerbay.com/infinitydb/manual

learn.microsoft.com/en-US/sql/sql-server

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.

Boiler Bay Inc.

Microsoft

Initial release

2015

2002

1989

Current release

3.1.0, July 2020

1.1, February 2017

4.0

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

All OS with a Java VM

Linux
Windows

Data scheme

yes

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

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

Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes, but depending on the SQL-Server Edition

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

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

yes, on a single node

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

fine grained access rights according to SQL-standard

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