DBMS > BaseX vs. Drizzle vs. NSDb vs. SAP Adaptive Server vs. Spark SQL

System Properties Comparison BaseX vs. Drizzle vs. NSDb vs. SAP Adaptive Server vs. Spark SQL

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

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

Primary database model

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

basex.org

nsdb.io

www.sap.com/products/technology-platform/sybase-ase.html

spark.apache.org/sql

Technical documentation

docs.basex.org

nsdb.io/Architecture

help.sap.com/docs/SAP_ASE

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

Developer

BaseX GmbH

Drizzle project, originally started by Brian Aker

SAP, Sybase

Apache Software Foundation

Initial release

2007

2008

2017

1987

2014

Current release

10.7, August 2023

7.2.4, September 2012

16.0

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

BSD license

Open Source

GNU GPL

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

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

C++

Java, Scala

C and C++

Scala

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux
macOS

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

SQL-like DML and DDL statements

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

JDBC

gRPC
HTTP REST
WebSocket

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

JDBC
ODBC

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

C
C++
Java
PHP

Java
Scala

C
C++
Cobol
Java
Java
Perl
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java and Transact-SQL

Triggers

yes

via events

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Using Apache Lucene

yes

In-memory capabilities

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

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Recent citations in the news

XML Injection Attacks: What to Know About XPath, XQuery, XXE & More
18 May 2022, Hashed Out by The SSL Store™

9 Skills You Need to Become a Data Engineer
2 November 2022, KDnuggets

provided by Google News

AWS Launch Wizard is now available in Melbourne, Spain, and Zurich Regions
26 January 2024, AWS Blog

Arcion Introduces SAP Sybase ASE Connector for Ultimate Migration Flexibility
5 January 2023, Business Wire

Patch SAP Adaptive Server Enterprise now to avoid takeover risk
3 June 2020, BleepingComputer

Newly Patched SAP ASE Flaws Could Let Attackers Hack Database Servers
3 June 2020, The Hacker News

Critical SAP ASE Flaws Allow Complete Control of Databases
3 June 2020, Threatpost

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

Share this page