DBMS > Axibase vs. Sadas Engine vs. SAP Advantage Database Server vs. Spark SQL vs. SpatiaLite

System Properties Comparison Axibase vs. Sadas Engine vs. SAP Advantage Database Server vs. Spark SQL vs. SpatiaLite

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Low-cost RDBMS with access to ISAM and FoxPro data structures

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

Spatial extension of SQLite

Primary database model

Time Series DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

axibase.com/docs/atsd/finance

www.sadasengine.com

www.sap.com/products/advantage-database-server.html

spark.apache.org/sql

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

Technical documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

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

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

Developer

Axibase Corporation

SADAS s.r.l.

Sybase, SAP

Apache Software Foundation

Alessandro Furieri

Initial release

2013

2006

1993

2014

2008

Current release

15585

8.0

3.5.0 ( 2.13), September 2023

5.0.0, August 2020

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free trial version available

commercial

Open Source

Apache 2.0

Open Source

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

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++

Scala

C++

Server operating systems

Linux

AIX
Linux
Windows

Linux
Windows

Linux
OS X
Windows

server-less

Data scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, 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

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

Delphi
Perl
PHP

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

managed by 'Learn by Usage'

caching of (temporary) tables can be configured

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

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

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

The Ultimate ATV Test: Suzuki's King Quad 750 AXI Rugged Package vs. Alaska's Hunting Season
14 October 2020, Outdoor Life

provided by Google News

SAP Announces Q3 2023 Results: Asia Pacific and Japan View
19 October 2023, SAP News

provided by Google News

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

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

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

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

Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM)
17 March 2024, Yahoo Singapore News

provided by Google News

Share this page