DBMS > Badger vs. Dgraph vs. Hawkular Metrics vs. Lovefield

System Properties Comparison Badger vs. Dgraph vs. Hawkular Metrics vs. Lovefield

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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.

Distributed and scalable native Graph DBMS

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Embeddable relational database for web apps written in pure JavaScript

Primary database model

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	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

github.com/dgraph-io/badger

dgraph.io

www.hawkular.org

google.github.io/lovefield

Technical documentation

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

dgraph.io/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

DGraph Labs

Dgraph Labs, Inc.

Community supported by Red Hat

Google

Initial release

2017

2016

2014

Current release

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

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

Java

JavaScript

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

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

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

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

HTTP REST

Supported programming languages

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

Go
Java
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

Triggers

yes

via Hawkular Alerting

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication via Raft

selectable replication factor

based on Cassandra

none

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

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Planned for future releases

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More resources

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