DBMS > Elasticsearch vs. HEAVY.AI vs. MarkLogic vs. Microsoft SQL Server vs. Prometheus

System Properties Comparison Elasticsearch vs. HEAVY.AI vs. MarkLogic vs. Microsoft SQL Server vs. Prometheus

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Operational and transactional Enterprise NoSQL database

Microsofts flagship relational DBMS

Open-source Time Series DBMS and monitoring system

Primary database model

Search engine

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Spatial 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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

www.elastic.co/elasticsearch

github.com/heavyai/heavydb
www.heavy.ai

www.marklogic.com

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

prometheus.io

Technical documentation

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

docs.heavy.ai

docs.marklogic.com

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

prometheus.io/docs

Developer

Elastic

HEAVY.AI, Inc.

MarkLogic Corp.

Microsoft

Initial release

2010

2016

2001

1989

2015

Current release

8.6, January 2023

5.10, January 2022

11.0, December 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

Apache 2.0

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++ and CUDA

C++

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

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

yes

schema-free

Schema can be enforced

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL92

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

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

RESTful HTTP/JSON API

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

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

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

yes, but depending on the SQL-Server Edition

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

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

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

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.

Memcached and Redis integration

yes

yes, with Range Indexes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

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