DBMS > EventStoreDB vs. Faircom EDGE vs. NSDb vs. SwayDB vs. TigerGraph

System Properties Comparison EventStoreDB vs. Faircom EDGE vs. NSDb vs. SwayDB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Event Store

Key-value store
Relational DBMS

Time Series DBMS

Key-value store

Graph DBMS

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

www.eventstore.com

www.faircom.com/products/faircom-edge

nsdb.io

swaydb.simer.au

www.tigergraph.com

Technical documentation

developers.eventstore.com

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

nsdb.io/Architecture

docs.tigergraph.com

Developer

Event Store Limited

FairCom Corporation

Simer Plaha

Initial release

2012

1979

2017

2018

2017

Current release

21.2, February 2021

V3, October 2020

License

Commercial or Open Source

Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

commercial

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.

Implementation language

ANSI C, C++

Java, Scala

Scala

C++

Server operating systems

Linux
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS

Linux

Data scheme

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

schema-free

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

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

gRPC
HTTP REST
WebSocket

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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

Java
Scala

Java
Kotlin
Scala

C++
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Relationships in graphs

Transaction concepts

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

ACID

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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.

Role-based access control

More information provided by the system vendor

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

Recent citations in the news

Innovative Software and Giant Lego Sets, Why FairCom Edge Booth is a Must-Visit at Automate
9 May 2024, MVPro

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

TigerGraph Unveils CoPilot, Version 4.0, and New CEO
30 April 2024, Datanami

TigerGraph unveils GenAI assistant, introduces new CEO
30 April 2024, TechTarget

How TigerGraph CoPilot enables graph-augmented AI
30 April 2024, InfoWorld

TigerGraph Bolsters DB for Enterprise Graph Workloads
1 November 2023, Datanami

Aerospike takes on Neo4j and TigerGraph with launch of graph database
20 June 2023, SiliconANGLE News

provided by Google News

Share this page