DBMS > Elasticsearch vs. Hive vs. Microsoft SQL Server vs. RDF4J vs. XTDB

System Properties Comparison Elasticsearch vs. Hive vs. Microsoft SQL Server vs. RDF4J vs. XTDB

Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Microsofts flagship relational DBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.elastic.co/elasticsearch

hive.apache.org

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

rdf4j.org

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

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

cwiki.apache.org/confluence/display/Hive/Home

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

rdf4j.org/documentation

www.xtdb.com/docs

Developer

Elastic

Apache Software Foundation

initially developed by Facebook

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Juxt Ltd.

Initial release

2010

2012

1989

2004

2019

Current release

8.6, January 2023

3.1.3, April 2022

SQL Server 2022, November 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache Version 2

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++

Java

Clojure

Server operating systems

All OS with a Java VM

Linux
Windows

Linux
OS X
Unix
Windows

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

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

RDF Schemas

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
ODBC
Thrift

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST
JDBC

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
PHP
Python

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

Java
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes, but depending on the SQL-Server Edition

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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.

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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