DBMS > Badger vs. Hazelcast vs. Lovefield vs. Realm

System Properties Comparison Badger vs. Hazelcast vs. Lovefield vs. Realm

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

A widely adopted in-memory data grid

Embeddable relational database for web apps written in pure JavaScript

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Key-value store

Relational DBMS

Document store

Secondary database models

Document store

JSON support with IMDG 3.12

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

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

github.com/dgraph-io/badger

hazelcast.com

google.github.io/lovefield

realm.io

Technical documentation

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

hazelcast.org/imdg/docs

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

realm.io/docs

Developer

DGraph Labs

Hazelcast

Google

Realm, acquired by MongoDB in May 2019

Initial release

2017

2008

2014

Current release

5.3.6, November 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

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

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

Android
Backend: server-less
iOS
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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

Supported programming languages

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

JavaScript

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Events

Using read-only observers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Replicated Map

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

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

yes

In-memory capabilities

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

yes

using MemoryDB

yes

In-Memory realm

User concepts

Access control

Role-based access control

yes

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More resources

DB-Engines blog posts

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2 March 2016, Paul Andlinger

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