DBMS > Bangdb vs. Microsoft Azure Table Storage vs. SAP SQL Anywhere vs. Snowflake vs. SQLite

System Properties Comparison Bangdb vs. Microsoft Azure Table Storage vs. SAP SQL Anywhere vs. Snowflake vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

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

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

Cloud-based data warehousing service for structured and semi-structured data

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

bangdb.com

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

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

www.snowflake.com

www.sqlite.org

Technical documentation

docs.bangdb.com

help.sap.com/docs/SAP_SQL_Anywhere

docs.snowflake.net/manuals/index.html

www.sqlite.org/docs.html

Developer

Sachin Sinha, BangDB

Microsoft

SAP

formerly Sybase

Snowflake Computing Inc.

Dwayne Richard Hipp

Initial release

2012

1992

2014

2000

Current release

BangDB 2.0, October 2021

17, July 2015

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Public Domain

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

C, C++

Server operating systems

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

hosted

server-less

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

dynamic column types

Typing

predefined data types such as float or date

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

yes

not rigid because of 'dynamic typing' concept.

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

SQL like support with command line tool

yes

SQL-92 is not fully supported

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

CLI Client
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Java
Python

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

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

JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

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

user defined functions

Triggers

yes, Notifications (with Streaming only)

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Implicit feature of the cloud service

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

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

Source-replica replication

Database mirroring

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

via file-system locks

Durability

Support for making data persistent

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, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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