DBMS > Hive vs. IBM Db2 Event Store vs. OpenEdge vs. SAP Adaptive Server vs. SQLite

System Properties Comparison Hive vs. IBM Db2 Event Store vs. OpenEdge vs. SAP Adaptive Server vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

Distributed Event Store optimized for Internet of Things use cases

Application development environment with integrated database management system

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

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

hive.apache.org

www.ibm.com/products/db2-event-store

www.progress.com/openedge

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

www.sqlite.org

Technical documentation

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

www.ibm.com/docs/en/db2-event-store

documentation.progress.com/output/ua/OpenEdge_latest

help.sap.com/docs/SAP_ASE

www.sqlite.org/docs.html

Developer

Apache Software Foundation

initially developed by Facebook

IBM

Progress Software Corporation

SAP, Sybase

Dwayne Richard Hipp

Initial release

2012

2017

1984

1987

2000

Current release

3.1.3, April 2022

2.0

OpenEdge 12.2, March 2020

16.0

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free developer edition available

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

through the embedded Spark runtime

yes

close to SQL 92

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
Thrift

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C++
Java
PHP
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Progress proprietary ABL (Advanced Business Language)

C
C++
Cobol
Java
Java
Perl
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

since Version 11.4

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Active-active shard replication

Source-replica replication

Multi-source replication
Source-replica replication

none

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

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

via file-system locks

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Users and groups

fine grained access rights according to SQL-standard

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