DBMS > Faircom EDGE vs. GeoSpock vs. OpenSearch vs. Spark SQL

System Properties Comparison Faircom EDGE vs. GeoSpock vs. OpenSearch vs. Spark SQL

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

Vector DBMS

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

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

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.faircom.com/products/faircom-edge

geospock.com

github.com/opensearch-project
opensearch.org

spark.apache.org/sql

Technical documentation

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

opensearch.org/docs/latest

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

FairCom Corporation

GeoSpock

Amazon Web Services

Apache Software Foundation

Initial release

1979

2021

2014

Current release

V3, October 2020

2.0, September 2019

2.5.0, January 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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.

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Implementation language

ANSI C, C++

Java, Javascript

Java

Scala

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

hosted

All OS with a Java VM

Linux
OS X
Windows

Data scheme

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

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Typing

predefined data types such as float or date

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

yes

temporal, categorical

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

ANSI SQL queries

ANSI SQL for query only (using Presto)

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

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

JDBC

Java API
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Automatic sharding

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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 rights for users can be defined per table

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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