DBMS > GeoSpock vs. HBase vs. SAP Adaptive Server vs. Spark SQL vs. STSdb

System Properties Comparison GeoSpock vs. HBase vs. SAP Adaptive Server vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Spatial and temporal data processing engine for extreme data scale

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Time Series DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.13
Rank	#307	Overall
	#141	Relational DBMS

Score	42.45
Rank	#26	Overall
	#2	Wide column stores

Score	44.82
Rank	#25	Overall
	#17	Relational DBMS

Score	23.72
Rank	#35	Overall
	#21	Relational DBMS

Score	0.00
Rank	#357	Overall
	#56	Key-value stores

Website

geospock.com

hbase.apache.org

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

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

docs.geospock.com/Content/Home.htm

hbase.apache.org

help.sap.com/viewer/product/SAP_ASE

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

Developer

GeoSpock

Apache Software Foundation

Apache top-level project, originally developed by Powerset

SAP, Sybase

Apache Software Foundation

STS Soft SC

Initial release

2008

1987

2014

2011

Current release

2.0, September 2019

2.3.4, January 2021

16.0

3.3.0, June 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Javascript

Java

C and C++

Scala

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux
OS X
Windows

Windows

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

primitive types and user defined types (classes)

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC

Java API
RESTful HTTP API
Thrift

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

JDBC
ODBC

.NET Client API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Cobol
Java
Java
Perl
PHP
Python

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
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

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

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

Access rights for users can be defined per table

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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