DBMS > BigchainDB vs. Faircom EDGE vs. GeoMesa vs. KairosDB vs. Microsoft SQL Server

System Properties Comparison BigchainDB vs. Faircom EDGE vs. GeoMesa vs. KairosDB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Distributed Time Series DBMS based on Cassandra or H2

Microsofts flagship relational DBMS

Primary database model

Document store

Key-value store
Relational DBMS

Spatial DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

www.bigchaindb.com

www.faircom.com/products/faircom-edge

www.geomesa.org

github.com/kairosdb/kairosdb

www.microsoft.com/en-us/sql-server

Technical documentation

bigchaindb.readthedocs.io/en/latest

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

www.geomesa.org/documentation/stable/user/index.html

kairosdb.github.io

learn.microsoft.com/en-US/sql/sql-server

Developer

FairCom Corporation

CCRi and others

Microsoft

Initial release

2016

1979

2014

2013

1989

Current release

V3, October 2020

5.0.0, May 2024

1.2.2, November 2018

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Restricted, free version available

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

ANSI C, C++

Scala

Java

C++

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

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

yes

schema-free

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

SQL

Support of SQL

yes

ANSI SQL queries

yes

APIs and other access methods

CLI Client
RESTful HTTP API

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

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

Java
JavaScript

Node.js
PHP
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

depending on storage layer

Sharding

based on Cassandra

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Synchronous and asynchronous realtime replication based on transaction logs

depending on storage layer

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

depending on storage layer

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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,with MongoDB ord RethinkDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

depending on storage layer

yes

User concepts

Access control

yes

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

yes

depending on the DBMS used for storage

simple password-based access control

fine grained access rights according to SQL-standard

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