DBMS > Apache Druid vs. BaseX vs. Postgres-XL vs. SpatiaLite vs. Teradata Aster

System Properties Comparison Apache Druid vs. BaseX vs. Postgres-XL vs. SpatiaLite vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Spatial extension of SQLite

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

druid.apache.org

basex.org

www.postgres-xl.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

druid.apache.org/docs/latest/design

docs.basex.org

www.postgres-xl.org/documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Apache Software Foundation and contributors

BaseX GmbH

Alessandro Furieri

Teradata

Initial release

2012

2007

2014

since 2012, originally named StormDB

2008

2005

Current release

29.0.1, April 2024

10.7, August 2023

10 R1, October 2018

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSD license

Open Source

Mozilla public license

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

Linux
macOS

server-less

Linux

Data scheme

yes

schema-less columns are supported

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

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

XML type, but no XML query functionality

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

user defined functions

R packages

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

MVCC

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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