DBMS > BaseX vs. Databend vs. GeoMesa vs. Spark SQL vs. Transbase

System Properties Comparison BaseX vs. Databend vs. GeoMesa vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Spark SQL is a component on top of 'Spark Core' for structured data processing

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

basex.org

github.com/datafuselabs/databend
www.databend.com

www.geomesa.org

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

Technical documentation

docs.basex.org

docs.databend.com

www.geomesa.org/documentation/stable/user/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

Developer

BaseX GmbH

Databend Labs

CCRi and others

Apache Software Foundation

Transaction Software GmbH

Initial release

2007

2021

2014

1987

Current release

10.7, August 2023

1.0.59, April 2023

5.0.0, May 2024

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

BSD license

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Rust

Scala

C and C++

Server operating systems

Linux
OS X
Windows

hosted
Linux
macOS

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

CLI Client
JDBC
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

Go
Java
JavaScript (Node.js)
Python
Rust

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

yes

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.

depending on storage layer

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Users with fine-grained authorization concept, user roles

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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