DBMS > AlaSQL vs. Bangdb vs. HBase vs. MySQL vs. SAP SQL Anywhere

System Properties Comparison AlaSQL vs. Bangdb vs. HBase vs. MySQL vs. SAP SQL Anywhere

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Widely used open source RDBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Wide column store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

github.com/AlaSQL/alasql

docs.bangdb.com

hbase.apache.org/book.html

dev.mysql.com/doc

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Andrey Gershun & Mathias R. Wulff

Sachin Sinha, BangDB

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

since 2010, originally MySQL AB, then Sun

SAP

formerly Sybase

Initial release

2014

2012

2008

1995

1992

Current release

BangDB 2.0, October 2021

2.3.4, January 2021

8.3.0, January 2024

17, July 2015

License

Commercial or Open Source

Open Source

MIT-License

Open Source

BSD 3

Open Source

Apache version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

JavaScript

C, C++

Java

C and C++

Server operating systems

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

Linux

Linux
Unix
Windows

using Cygwin

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

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

options to bring your own types, AVRO

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

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

yes

with proprietary extensions

yes

APIs and other access methods

JavaScript API

Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

JavaScript

C
C#
C++
Java
Python

C
C#
C++
Groovy
Java
PHP
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

proprietary syntax

yes, in C/C++, Java, .Net or Perl

Triggers

yes

yes, Notifications (with Streaming only)

yes

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable consistency, set CAP knob accordingly

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Single row ACID (across millions of columns)

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

table locks or row locks depending on storage engine

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

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

User concepts

Access control

yes (enterprise version only)

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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