DBMS > InterSystems Caché vs. Oracle Berkeley DB vs. Postgres-XL vs. RocksDB vs. SAP Advantage Database Server

System Properties Comparison InterSystems Caché vs. Oracle Berkeley DB vs. Postgres-XL vs. RocksDB vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

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

Description

A multi-model DBMS and application server

Widely used in-process key-value store

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.intersystems.com/products/cache

www.oracle.com/database/technologies/related/berkeleydb.html

www.postgres-xl.org

rocksdb.org

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

Technical documentation

docs.intersystems.com

docs.oracle.com/cd/E17076_05/html/index.html

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

Developer

InterSystems

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Facebook, Inc.

Sybase, SAP

Initial release

1997

1994

2014

since 2012, originally named StormDB

2013

1993

Current release

2018.1.4, May 2020

18.1.40, May 2020

10 R1, October 2018

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Mozilla public license

Open Source

BSD

commercial

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

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS

Linux

Linux
Windows

Data scheme

depending on used data model

schema-free

yes

schema-free

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

only with the Berkeley DB XML edition

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

distributed, parallel query execution

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
RESTful HTTP API

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

C++ API
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C#
C++
Java

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

C
C++
Go
Java
Perl
Python
Ruby

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

MVCC

yes

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

caching of (temporary) tables can be configured

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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