DBMS > Faircom EDGE vs. GeoSpock vs. Rockset vs. Snowflake vs. XTDB

System Properties Comparison Faircom EDGE vs. GeoSpock vs. Rockset vs. Snowflake vs. XTDB

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 scalable, reliable search and analytics service in the cloud, built on RocksDB

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

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

Primary database model

Key-value store
Relational DBMS

Secondary database models

Time Series DBMS

Relational DBMS
Search engine

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	0.82
Rank	#212	Overall
	#36	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.faircom.com/products/faircom-edge

geospock.com

rockset.com

www.snowflake.com

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

Technical documentation

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

docs.rockset.com

docs.snowflake.net/manuals/index.html

www.xtdb.com/docs

Developer

FairCom Corporation

GeoSpock

Rockset

Snowflake Computing Inc.

Juxt Ltd.

Initial release

1979

2019

2014

2019

Current release

V3, October 2020

2.0, September 2019

1.19, September 2021

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

MIT License

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

ANSI C, C++

Java, Javascript

C++

Clojure

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

hosted

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

Data scheme

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

yes

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

dynamic typing

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

ingestion from XML files supported

yes

Secondary indexes

yes

temporal, categorical

all fields are automatically indexed

yes

SQL

Support of SQL

yes

ANSI SQL queries

ANSI SQL for query only (using Presto)

Read-only SQL queries, including JOINs

yes

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

JDBC

HTTP REST

CLI Client
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

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

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Automatic sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

yes, each node contains all data

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

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

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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.

Access rights for users can be defined per table

Access rights for users and organizations can be defined via Rockset console

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

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