DBMS > Badger vs. Microsoft Azure Synapse Analytics vs. OrientDB vs. WakandaDB

System Properties Comparison Badger vs. Microsoft Azure Synapse Analytics vs. OrientDB vs. WakandaDB

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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.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Multi-model DBMS (Document, Graph, Key/Value)

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store

Object oriented DBMS

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

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

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

github.com/dgraph-io/badger

azure.microsoft.com/services/synapse-analytics

orientdb.org

wakanda.github.io

Technical documentation

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

docs.microsoft.com/azure/synapse-analytics

www.orientdb.com/docs/last/index.html

wakanda.github.io/doc

Developer

DGraph Labs

Microsoft

OrientDB LTD; CallidusCloud; SAP

Wakanda SAS

Initial release

2017

2016

2010

2012

Current release

3.2.29, March 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache version 2

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++, JavaScript

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

All OS with a Java JDK (>= JDK 6)

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language, no joins

APIs and other access methods

ADO.NET
JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

C#
Java
PHP

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

Transact SQL

Java, Javascript

yes

Triggers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

relationship in graphs

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.

User concepts

Access control

yes

Access rights for users and roles; record level security configurable

yes

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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