DBMS > EJDB vs. Fauna vs. Snowflake vs. SQream DB

System Properties Comparison EJDB vs. Fauna vs. Snowflake vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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.

Cloud-based data warehousing service for structured and semi-structured data

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

github.com/Softmotions/ejdb

fauna.com

www.snowflake.com

sqream.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.fauna.com

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

Softmotions

Fauna, Inc.

Snowflake Computing Inc.

SQream Technologies

Initial release

2012

2014

2017

Current release

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

GPLv2

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

Scala

C++, CUDA, Haskell, Java, Scala

Server operating systems

server-less

hosted

Linux

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

RESTful HTTP API

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

user defined functions in Python

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

consistent hashing

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Identity management, authentication, and access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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