DBMS > Hive vs. Postgres-XL vs. SAP Adaptive Server vs. SAP HANA

System Properties Comparison Hive vs. Postgres-XL vs. SAP Adaptive Server vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

hive.apache.org

www.postgres-xl.org

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

www.sap.com/products/hana.html

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

www.postgres-xl.org/documentation

help.sap.com/docs/SAP_ASE

help.sap.com/hana

Developer

Apache Software Foundation

initially developed by Facebook

SAP, Sybase

SAP

Initial release

2012

2014

since 2012, originally named StormDB

1987

2010

Current release

3.1.3, April 2022

10 R1, October 2018

16.0

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Mozilla public license

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

Linux
macOS

AIX
HP-UX
Linux
Solaris
Unix
Windows

Appliance or cloud-service

Data scheme

yes

Typing

predefined data types such as float or date

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
ODBC
Thrift

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

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

JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Java and Transact-SQL

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

yes

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