DBMS > HarperDB vs. MarkLogic vs. Microsoft SQL Server vs. OpenEdge vs. searchxml

System Properties Comparison HarperDB vs. MarkLogic vs. Microsoft SQL Server vs. OpenEdge vs. searchxml

Editorial information provided by DB-Engines

Name

Description

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

Operational and transactional Enterprise NoSQL database

Microsofts flagship relational DBMS

Application development environment with integrated database management system

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Native XML DBMS
Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	4.15
Rank	#70	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#8	Search engines

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

www.harperdb.io

www.progress.com/marklogic

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

www.progress.com/openedge

www.searchxml.net/category/products

Technical documentation

docs.harperdb.io/docs

www.progress.com/marklogic/documentation

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

documentation.progress.com/output/ua/OpenEdge_latest

www.searchxml.net/support/handouts

Developer

HarperDB

MarkLogic Corp.

Microsoft

Progress Software Corporation

informationpartners gmbh

Initial release

2017

2001

1989

1984

2015

Current release

3.1, August 2021

11.0, December 2022

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

1.0

License

Commercial or Open Source

commercial

free community edition available

commercial

restricted free version is available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Node.js

C++

Server operating systems

Linux
OS X

Linux
OS X
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Windows

Data scheme

dynamic schema

schema-free

Schema can be enforced

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL-like data manipulation statements

yes

SQL92

yes

close to SQL 92

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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)

JDBC
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Progress proprietary ABL (Advanced Business Language)

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

via XQuery or JavaScript

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

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

A table resides as a whole on one (or more) nodes in a cluster

Sharding

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

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

yes

yes, but depending on the SQL-Server Edition

Source-replica replication

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using LMDB

yes

In-memory capabilities

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

yes

yes, with Range Indexes

yes

User concepts

Access control

Access rights for users and roles

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

Users and groups

Domain, group and role-based access control at the document level and for application services

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