DBMS > Bangdb vs. FeatureBase vs. KairosDB vs. Microsoft SQL Server vs. Valentina Server

System Properties Comparison Bangdb vs. FeatureBase vs. KairosDB vs. Microsoft SQL Server vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Distributed Time Series DBMS based on Cassandra or H2

Microsofts flagship relational DBMS

Object-relational database and reports server

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Relational 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	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

bangdb.com

www.featurebase.com

github.com/kairosdb/kairosdb

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

www.valentina-db.net

Technical documentation

docs.bangdb.com

docs.featurebase.com

kairosdb.github.io

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

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Sachin Sinha, BangDB

Molecula and Pilosa Open Source Contributors

Microsoft

Paradigma Software

Initial release

2012

2017

2013

1989

1999

Current release

BangDB 2.0, October 2021

2022, May 2022

1.2.2, November 2018

SQL Server 2022, November 2022

5.7.5

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C, C++

Java

C++

Server operating systems

Linux

Linux
macOS

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

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

SQL like support with command line tool

SQL queries

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

gRPC
JDBC
Kafka Connector
ODBC

Graphite protocol
HTTP REST
Telnet API

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

ODBC

Supported programming languages

C
C#
C++
Java
Python

Java
Python

Java
JavaScript

Node.js
PHP
Python

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

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

yes

Triggers

yes, Notifications (with Streaming only)

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

based on Cassandra

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)

yes

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

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

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

ACID

yes

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, using Linux fsync

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)

simple password-based access control

fine grained access rights according to SQL-standard

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