DBMS > Faircom EDGE vs. Heroic vs. NSDb vs. SwayDB vs. Tigris

System Properties Comparison Faircom EDGE vs. Heroic vs. NSDb vs. SwayDB vs. Tigris

Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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 horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Key-value store

Document store
Key-value store
Search engine
Time Series 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	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

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

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

www.faircom.com/products/faircom-edge

github.com/spotify/heroic

nsdb.io

swaydb.simer.au

www.tigrisdata.com

Technical documentation

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

spotify.github.io/heroic

nsdb.io/Architecture

www.tigrisdata.com/docs

Developer

FairCom Corporation

Spotify

Simer Plaha

Tigris Data, Inc.

Initial release

1979

2014

2017

2018

2022

Current release

V3, October 2020

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

Open Source

Apache Version 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.

Implementation language

ANSI C, C++

Java

Java, Scala

Scala

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS

Linux
macOS
Windows

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

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

via Elasticsearch

all fields are automatically indexed

yes

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like query language

APIs and other access methods

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

gRPC
HTTP REST
WebSocket

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

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

Java
Scala

Java
Kotlin
Scala

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

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

yes, using FoundationDB

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 and roles

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