DBMS > Badger vs. H2GIS vs. Microsoft SQL Server vs. MonetDB vs. Tarantool

System Properties Comparison Badger vs. H2GIS vs. Microsoft SQL Server vs. MonetDB vs. Tarantool

Editorial information provided by DB-Engines

Name

Description

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

Spatial extension of H2

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Key-value store

Spatial DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Spatial DBMS

with Tarantool/GIS extension

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

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Website

github.com/dgraph-io/badger

www.h2gis.org

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

www.monetdb.org

www.tarantool.io

Technical documentation

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

www.h2gis.org/docs/home

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

www.monetdb.org/Documentation

www.tarantool.io/en/doc

Developer

DGraph Labs

CNRS

Microsoft

MonetDB BV

Initial release

2017

2013

1989

2004

2008

Current release

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

LGPL 3.0

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
macOS

Data scheme

schema-free

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

yes

SQL 2003 with some extensions

Full-featured ANSI SQL support

APIs and other access methods

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Open binary protocol

Supported programming languages

Java

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

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

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

based on H2

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

yes, in SQL, C, R

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding via remote tables

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

based on H2

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

yes

based on H2

fine grained access rights according to SQL-standard

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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