DBMS > AlaSQL vs. Bangdb vs. Quasardb vs. TimesTen

System Properties Comparison AlaSQL vs. Bangdb vs. Quasardb vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Converged and high performance database for device data, events, time series, document and graph

Distributed, high-performance timeseries database

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

alasql.org

bangdb.com

quasar.ai

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

Technical documentation

github.com/AlaSQL/alasql

docs.bangdb.com

doc.quasar.ai/master

docs.oracle.com/database/timesten-18.1

Developer

Andrey Gershun & Mathias R. Wulff

Sachin Sinha, BangDB

quasardb

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2014

2012

2009

1998

Current release

BangDB 2.0, October 2021

3.14.1, January 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

MIT-License

Open Source

BSD 3

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

JavaScript

C, C++

C++

Server operating systems

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

Linux

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

integer and binary

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

with tags

yes

SQL

Support of SQL

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

SQL like support with command line tool

SQL-like query language

yes

APIs and other access methods

JavaScript API

Proprietary protocol
RESTful HTTP API

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

JavaScript

C
C#
C++
Java
Python

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

PL/SQL

Triggers

yes

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes, implements WAL (Write ahead log) as well

yes

by using LevelDB

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

Transient mode

yes

User concepts

Access control

yes (enterprise version only)

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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