DBMS > EsgynDB vs. Faircom DB vs. InfluxDB vs. OrientDB vs. VoltDB

System Properties Comparison EsgynDB vs. Faircom DB vs. InfluxDB vs. OrientDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

DBMS for storing time series, events and metrics

Multi-model DBMS (Document, Graph, Key/Value)

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	22.12
Rank	#28	Overall
	#1	Time Series DBMS

Score	3.02
Rank	#88	Overall
	#16	Document stores
	#6	Graph DBMS
	#12	Key-value stores

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

www.esgyn.cn

www.faircom.com/products/faircom-db

www.influxdata.com/products/influxdb-overview

orientdb.org

www.voltdb.com

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.influxdata.com/influxdb

www.orientdb.com/docs/last/index.html

docs.voltdb.com

Developer

Esgyn

FairCom Corporation

OrientDB LTD; CallidusCloud; SAP

VoltDB Inc.

Initial release

2015

1979

2013

2010

Current release

V13, July 2024

2.7.6, April 2024

3.2.29, March 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache version 2

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

C++, Java

ANSI C, C++

Java

Java, C++

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
OS X

through Homebrew

All OS with a Java JDK (>= JDK 6)

Linux
OS X

for development

Data scheme

yes

schema free, schema optional, schema required, partial schema,

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

Numeric data and Strings

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.

Secondary indexes

yes

SQL

Support of SQL

yes

yes, ANSI SQL with proprietary extensions

SQL-like query language

SQL-like query language, no joins

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

HTTP API
JSON over UDP

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

Java, Javascript

Java

Triggers

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

in enterprise version only

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

selectable replication factor

in enterprise version only

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Foreign keys

Referential integrity

yes

relationship in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

Snapshots and command logging

In-memory capabilities

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

yes

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

Fine grained access rights according to SQL-standard with additional protections for files

simple rights management via user accounts

Access rights for users and roles; record level security configurable

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

Deploying InfluxDB and Telegraf to Monitor Kubernetes
17 September 2024

Telegraf 1.32 Release Notes
13 September 2024

An Introductory Guide to Cloud Security for IIoT
12 September 2024

Building Real-Time Android Apps with InfluxDB Cloud: Data Logging, Querying, and Visualization
10 September 2024

How to Use InfluxDB for Real-Time SpringBoot Application Monitoring
5 September 2024

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

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

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

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

InfluxData's Latest Updates Optimize Time Series Data for Better Performance, Scale and Management
19 September 2024, Integration Developers

Run and manage open source InfluxDB databases with Amazon Timestream
14 March 2024, AWS Blog

InfluxData avoids ’AI magic beans’ in InfluxDB time series database update for enterprises
4 September 2024, VentureBeat

InfluxData Enhances InfluxDB 3.0 with Performance Upgrades and Self-Managed Option
5 September 2024, Datanami

InfluxData makes performance, storage improvements to InfluxDB 3.0
4 September 2024, InfoWorld

provided by Google News

Top 8 Best NoSQL Databases in 2024
9 September 2024, AIM

OrientDB: A Flexible and Scalable Multi-Model NoSQL DBMS
21 January 2022, Open Source For You

Comparing Graph Databases II. Part 2: ArangoDB, OrientDB, and… | by Sam Bell
20 September 2019, Towards Data Science

ArangoDB raises $10 million for NoSQL database management
14 March 2019, VentureBeat

The 12 Best Graph Databases to Consider for 2024
22 October 2023, Solutions Review

provided by Google News

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

Unveiling Volt Active Data’s game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Aims for Fast Big Data Development
29 January 2015, ADT Magazine

Solutions Review Sits Down with VoltDB CEO David Flower
17 April 2018, Solutions Review

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

provided by Google News

Share this page