DBMS > AlaSQL vs. Microsoft Azure Table Storage vs. Oracle vs. Oracle Berkeley DB vs. TerarkDB

System Properties Comparison AlaSQL vs. Microsoft Azure Table Storage vs. Oracle vs. Oracle Berkeley DB vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used RDBMS

Widely used in-process key-value store

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store
Relational DBMS

Wide column store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

alasql.org

azure.microsoft.com/en-us/services/storage/tables

www.oracle.com/database

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

github.com/bytedance/terarkdb

Technical documentation

github.com/AlaSQL/alasql

docs.oracle.com/en/database

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Andrey Gershun & Mathias R. Wulff

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

ByteDance, originally Terark

Initial release

2014

2012

1980

1994

2016

Current release

23c, September 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

MIT-License

commercial

restricted free version is available

Open Source

commercial license available

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

C and C++

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

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JavaScript API

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

C++ API
Java API

Supported programming languages

JavaScript

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.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

C++
Java

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

optimistic locking

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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