DBMS > Faircom EDGE vs. Firebase Realtime Database vs. H2 vs. Vertica vs. XTDB

System Properties Comparison Faircom EDGE vs. Firebase Realtime Database vs. H2 vs. Vertica vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Relational DBMS

Document store

Relational DBMS

Column oriented

Document store

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.faircom.com/products/faircom-edge

firebase.google.com/products/realtime-database

www.h2database.com

www.vertica.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

firebase.google.com/docs/database

www.h2database.com/html/main.html

vertica.com/documentation

www.xtdb.com/docs

Developer

FairCom Corporation

Google

acquired by Google 2014

Thomas Mueller

OpenText

previously Micro Focus and Hewlett Packard

Juxt Ltd.

Initial release

1979

2012

2005

2019

Current release

V3, October 2020

2.2.220, July 2023

12.0.3, January 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Limited community edition free

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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++

Clojure

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

hosted

All OS with a Java VM

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

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

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

yes, extensible-data-notation format

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

SQL

Support of SQL

yes

ANSI SQL queries

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

limited SQL, making use of Apache Calcite

APIs and other access methods

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

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

HTTP REST
JDBC

Supported programming languages

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

Java
JavaScript
Objective-C

Java

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Clojure
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

limited functionality with using 'rules'

Java Stored Procedures and User-Defined Functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Callbacks are triggered when data changes

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

none

horizontal partitioning, hierarchical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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.

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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