DBMS > Bangdb vs. HBase vs. Hypertable vs. Microsoft SQL Server vs. TempoIQ

System Properties Comparison Bangdb vs. HBase vs. Hypertable vs. Microsoft SQL Server vs. TempoIQ

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Microsofts flagship relational DBMS

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Document store
Graph DBMS
Time Series DBMS

Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

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

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

bangdb.com

hbase.apache.org

www.microsoft.com/en-us/sql-server

tempoiq.com (offline)

Technical documentation

docs.bangdb.com

hbase.apache.org/book.html

learn.microsoft.com/en-US/sql/sql-server

Developer

Sachin Sinha, BangDB

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Hypertable Inc.

Microsoft

TempoIQ

Initial release

2012

2008

2009

1989

2012

Current release

BangDB 2.0, October 2021

2.3.4, January 2021

0.9.8.11, March 2016

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache version 2

Open Source

GNU version 3. Commercial license available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++

Java

C++

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

Data scheme

schema-free

schema-free, schema definition possible

schema-free

yes

schema-free

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

C++ API
Thrift

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API

Supported programming languages

C
C#
C++
Java
Python

C
C#
C++
Groovy
Java
PHP
Python
Scala

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes, Notifications (with Streaming only)

yes

Realtime Alerts

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

selectable replication factor on file system level

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

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

fine grained access rights according to SQL-standard

simple authentication-based access control

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