DBMS > CrateDB vs. Faircom EDGE vs. FatDB vs. Graphite

System Properties Comparison CrateDB vs. Faircom EDGE vs. FatDB vs. Graphite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Distributed Database based on Lucene

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Key-value store
Relational DBMS

Document store
Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.73
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

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

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Website

cratedb.com

www.faircom.com/products/faircom-edge

github.com/graphite-project/graphite-web

Technical documentation

cratedb.com/docs

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

graphite.readthedocs.io

Developer

Crate

FairCom Corporation

FatCloud

Chris Davis

Initial release

2013

1979

2012

2006

Current release

V3, October 2020

License

Commercial or Open Source

Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache 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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

Java

ANSI C, C++

Python

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Android
Linux

ARM, x86
Raspbian
Windows

Windows

Linux
Unix

Data scheme

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

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

Numeric data only

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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

ANSI SQL queries

Via inetgration in SQL Server

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

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

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API
Sockets

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

.Net, JavaScript, C/C++

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

locking

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

rights management via user accounts

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

Can implement custom security layer via applications

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
» more

Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more

Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more

Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
» more

Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more

Licensing and pricing models

See CrateDB pricing >
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT
25 March 2024, PR Newswire

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
8 April 2024, Datanami

CrateDB Appoints Sergey Gerasimenko as New CTO
19 February 2024, AiThority

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

Real-Time Analytics Database Company CrateDB Names Lars Färnström as New CEO
1 March 2023, Business Wire

provided by Google News

Data Technology Company FairCom Expands The Edge with 2 New Releases of its Edge Computing Products
19 April 2023, Yahoo Finance

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

Brokers, Protocols, Platform Move Manufacturing Data
26 July 2023, EE Times

Winners of the 2021 IoT Evolution Product of the Year Awards Announced
6 July 2021, IoT Evolution World

Trend-Setting Products in Data and Information Management for 2023
8 December 2022, Database Trends and Applications

provided by Google News

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

The value of time series data and TSDBs
10 June 2021, InfoWorld

InfluxDB: From Open Source Time Series Database to Millions in Revenue
3 March 2021, hackernoon.com

Getting Started with Infrastructure Monitoring
11 September 2023, The New Stack

provided by Google News

Share this page