DBMS > Apache Kylin vs. GridGain vs. Microsoft SQL Server vs. Neo4j vs. XTDB

System Properties Comparison Apache Kylin vs. GridGain vs. Microsoft SQL Server vs. Neo4j vs. XTDB

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

GridGain is an in-memory computing platform, built on Apache Ignite

Microsofts flagship relational DBMS

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS

Document store

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	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

kylin.apache.org

www.gridgain.com

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

neo4j.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

kylin.apache.org/docs

www.gridgain.com/docs/index.html

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

neo4j.com/docs

www.xtdb.com/docs

Developer

Apache Software Foundation, originally contributed from eBay Inc

GridGain Systems, Inc.

Microsoft

Neo4j, Inc.

Juxt Ltd.

Initial release

2015

2007

1989

2007

2019

Current release

3.1.0, July 2020

GridGain 8.5.1

SQL Server 2022, November 2022

5.20, May 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

GPL version3, commercial licenses available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, C++, .Net

C++

Java, Scala

Clojure

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free and schema-optional

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

ANSI-99 for query and DML statements, subset of DDL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

HTTP REST
JDBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

Clojure
Java

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

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

yes

User defined Procedures and Functions

Triggers

yes (cache interceptors and events)

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes using Neo4j Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes, but depending on the SQL-Server Edition

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Foreign keys

Referential integrity

yes

Relationships in graphs

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

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Licensing and pricing models

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