DBMS > Badger vs. Hive vs. Microsoft SQL Server vs. VelocityDB

System Properties Comparison Badger vs. Hive vs. Microsoft SQL Server vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Microsofts flagship relational DBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Key-value store

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

github.com/dgraph-io/badger

hive.apache.org

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

velocitydb.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

cwiki.apache.org/confluence/display/Hive/Home

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

velocitydb.com/UserGuide

Developer

DGraph Labs

Apache Software Foundation

initially developed by Facebook

Microsoft

VelocityDB Inc

Initial release

2017

2012

1989

2011

Current release

3.1.3, April 2022

SQL Server 2022, November 2022

7.x

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
Windows

Any that supports .NET

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Thrift

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

.Net

Supported programming languages

C++
Java
PHP
Python

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

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Based on Windows Authentication

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