DBMS > AlaSQL vs. Hawkular Metrics vs. Infobright vs. MarkLogic vs. Oracle Berkeley DB

System Properties Comparison AlaSQL vs. Hawkular Metrics vs. Infobright vs. MarkLogic vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Operational and transactional Enterprise NoSQL database

Widely used in-process key-value store

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

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

Website

alasql.org

www.hawkular.org

ignitetech.com/softwarelibrary/infobrightdb

www.marklogic.com

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

Technical documentation

github.com/AlaSQL/alasql

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.marklogic.com

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

Developer

Andrey Gershun & Mathias R. Wulff

Community supported by Red Hat

Ignite Technologies Inc.; formerly InfoBright Inc.

MarkLogic Corp.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2014

2005

2001

1994

Current release

11.0, December 2022

18.1.40, May 2020

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

restricted free version is available

Open Source

commercial license available

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

JavaScript

Java

C++

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

Server operating systems

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

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

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

yes

SQL92

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JavaScript API

HTTP REST

ADO.NET
JDBC
ODBC

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

JavaScript

Go
Java
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

.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

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

Triggers

yes

via Hawkular Alerting

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

ACID

can act as a resource manager in an XA/JTA transaction

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

yes, with Range Indexes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Role-based access control at the document and subdocument levels

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