DBMS > AlaSQL vs. Cassandra vs. EJDB vs. Faircom EDGE vs. GridGain

System Properties Comparison AlaSQL vs. Cassandra vs. EJDB vs. Faircom EDGE vs. GridGain

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

GridGain is an in-memory computing platform, built on Apache Ignite

Primary database model

Document store
Relational DBMS

Wide column store

Document store

Key-value store
Relational DBMS

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

Score	0.55
Rank	#230	Overall
	#35	Document stores
	#111	Relational DBMS

Score	118.01
Rank	#11	Overall
	#1	Wide column stores

Score	0.10
Rank	#314	Overall
	#41	Document stores

Score	0.13
Rank	#304	Overall
	#44	Key-value stores
	#139	Relational DBMS

Score	2.06
Rank	#125	Overall
	#25	Key-value stores
	#61	Relational DBMS

Website

alasql.org

cassandra.apache.org

ejdb.org

www.faircom.com/products/faircomedge-iot-database

www.gridgain.com

Technical documentation

github.com/agershun/alasql

cassandra.apache.org/doc/latest

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

learn.faircomcorp.com/developers/documentation_directory

www.gridgain.com/docs/latest

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Apache top level project, originally developped by Facebook

Softmotions

FairCom Corporation

GridGain Systems, Inc.

Initial release

2014

2008

2012

1979

2007

Current release

4.0.4, May 2022

V3, October 2020

GridGain 8.5.1

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache version 2

Open Source

GPLv2

commercial

Restricted, free version available

commercial

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

JavaScript

Java

ANSI C, C++

Java, C++, .Net

Server operating systems

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

BSD
Linux
OS X
Windows

server-less

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI Standard SQL Types

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like SELECT, DML and DDL statements (CQL)

yes

ANSI SQL queries

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JavaScript API

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

in-process shared library

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

JavaScript

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

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

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

none

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Representation of geographical distribution of servers is possible

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

when using SQL

Transaction concepts

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

yes

only for local storage and DOM-storage

Atomicity and isolation are supported for single operations

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

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Access rights for users can be defined per object

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

Security Hooks for custom implementations

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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