DBMS > BaseX vs. Microsoft SQL Server vs. OpenEdge vs. Vertica

System Properties Comparison BaseX vs. Microsoft SQL Server vs. OpenEdge vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Microsofts flagship relational DBMS

Application development environment with integrated database management system

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Native XML DBMS

Relational DBMS

Column oriented

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	1.90
Rank	#136	Overall
	#4	Native XML DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	3.75
Rank	#88	Overall
	#47	Relational DBMS

Score	11.40
Rank	#43	Overall
	#27	Relational DBMS

Website

basex.org

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

www.progress.com/openedge

www.vertica.com

Technical documentation

docs.basex.org

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

documentation.progress.com/output/ua/OpenEdge_latest

vertica.com/documentation

Developer

BaseX GmbH

Microsoft

Progress Software Corporation

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2007

1989

1984

2005

Current release

10.7, August 2023

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

12.0.3, January 2023

License

Commercial or Open Source

Open Source

BSD license

commercial

restricted free version is available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

XQuery supports 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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

close to SQL 92

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

JDBC
ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

Progress proprietary ABL (Advanced Business Language)

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

Server-side scripts

Stored procedures

yes

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

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

via events

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

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

horizontal partitioning

since Version 11.4

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, but depending on the SQL-Server Edition

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

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

multiple readers, single writer

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

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

Users and groups

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
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