DBMS > EJDB vs. Faircom EDGE vs. InfinityDB vs. YTsaurus

System Properties Comparison EJDB vs. Faircom EDGE vs. InfinityDB vs. YTsaurus

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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)

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

A Java embedded Key-Value Store which extends the Java Map interface

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Document store

Key-value store
Relational DBMS

Key-value store

Document store
Key-value store

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

github.com/Softmotions/ejdb

www.faircom.com/products/faircom-edge

boilerbay.com

ytsaurus.tech

Technical documentation

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

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

boilerbay.com/infinitydb/manual

ytsaurus.tech/docs/en

Developer

Softmotions

FairCom Corporation

Boiler Bay Inc.

Yandex

Initial release

2012

1979

2002

2023

Current release

V3, October 2020

4.0

License

Commercial or Open Source

Open Source

GPLv2

commercial

Restricted, free version available

commercial

Open Source

Apache License, Version 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

ANSI C, C++

Java

C++

Server operating systems

server-less

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM

Ubuntu

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI Standard SQL Types

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

ANSI SQL queries

YQL, an SQL-based language, is supported

APIs and other access methods

in-process shared library

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Supported programming languages

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

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Java

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

when using SQL

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

across SQL and NoSQL

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Access Control Lists

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