DBMS > Badger vs. Microsoft SQL Server vs. Oracle Coherence vs. XTDB

System Properties Comparison Badger vs. Microsoft SQL Server vs. Oracle Coherence vs. XTDB

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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.

Microsofts flagship relational DBMS

Oracles in-memory data grid solution

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/dgraph-io/badger

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

www.oracle.com/java/coherence

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

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

docs.oracle.com/en/middleware/standalone/coherence

www.xtdb.com/docs

Developer

DGraph Labs

Microsoft

Oracle

Juxt Ltd.

Initial release

2017

1989

2007

2019

Current release

SQL Server 2022, November 2022

14.1, August 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Clojure

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

All OS with a Java VM

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

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

JCache
JPA
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

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

.Net
C++
Java

Clojure
Java

Server-side scripts

Stored procedures

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

Triggers

yes

Live 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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

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