DBMS > Badger vs. Dgraph vs. Microsoft Azure Synapse Analytics vs. Netezza vs. Valentina Server

System Properties Comparison Badger vs. Dgraph vs. Microsoft Azure Synapse Analytics vs. Netezza vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

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

Distributed and scalable native Graph DBMS

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

Data warehouse and analytics appliance part of IBM PureSystems

Object-relational database and reports server

Primary database model

Key-value store

Graph DBMS

Relational DBMS

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

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

github.com/dgraph-io/badger

dgraph.io

azure.microsoft.com/services/synapse-analytics

www.ibm.com/products/netezza

www.valentina-db.net

Technical documentation

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

dgraph.io/docs

docs.microsoft.com/azure/synapse-analytics

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

Developer

DGraph Labs

Dgraph Labs, Inc.

Microsoft

IBM

Paradigma Software

Initial release

2017

2016

2000

1999

Current release

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

Linux

included in appliance

Linux
OS X
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC
OLE DB

ODBC

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
Java
PHP

C
C++
Fortran
Java
Lua
Perl
Python
R

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

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication via Raft

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

Planned for future releases

yes

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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