DBMS > Fauna vs. Hazelcast vs. LevelDB

System Properties Comparison Fauna vs. Hazelcast vs. LevelDB

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Editorial information provided by DB-Engines

Name

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

A widely adopted in-memory data grid

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Key-value 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	1.55
Rank	#154	Overall
	#26	Document stores
	#14	Graph DBMS
	#72	Relational DBMS
	#13	Time Series DBMS

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Website

fauna.com

hazelcast.com

github.com/google/leveldb

Technical documentation

docs.fauna.com

hazelcast.org/imdg/docs

github.com/google/leveldb/blob/main/doc/index.md

Developer

Fauna, Inc.

Hazelcast

Google

Initial release

2014

2008

2011

Current release

5.3.6, November 2023

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

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

Scala

Java

C++

Server operating systems

hosted

All OS with a Java VM

Illumos
Linux
OS X
Windows

Data scheme

schema-free

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

APIs and other access methods

RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

user defined functions

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

Immediate Consistency

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

ACID

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

In-memory capabilities

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

yes

User concepts

Access control

Identity management, authentication, and access control

Role-based access control

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