DBMS > EsgynDB vs. HEAVY.AI vs. Immudb vs. Infobright vs. SpatiaLite

System Properties Comparison EsgynDB vs. HEAVY.AI vs. Immudb vs. Infobright vs. SpatiaLite

Editorial information provided by DB-Engines

Name

Description

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Spatial extension of SQLite

Primary database model

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

www.esgyn.cn

github.com/heavyai/heavydb
www.heavy.ai

github.com/codenotary/immudb
immudb.io

ignitetech.com/softwarelibrary/infobrightdb

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.heavy.ai

docs.immudb.io

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Esgyn

HEAVY.AI, Inc.

Codenotary

Ignite Technologies Inc.; formerly InfoBright Inc.

Alessandro Furieri

Initial release

2015

2016

2020

2005

2008

Current release

5.10, January 2022

1.2.3, April 2022

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

C++ and CUDA

C++

Server operating systems

Linux

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
Windows

server-less

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like syntax

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

gRPC protocol
PostgreSQL wire protocol

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Multi-source replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

HEAVY.AI: The Fastest Analytics and Location Intelligence Platform
1 March 2022, heavy.ai

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, businesswire.com

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

Making the most of geospatial intelligence
14 April 2023, InfoWorld

provided by Google News

Codenotary brings its immutable database to the cloud
21 June 2023, TechCrunch

ImmuDB and Codenotary: It's a database, but the company isn't
20 December 2021, ZDNet

Immudb: Open-source database, built on a zero trust model
17 December 2021, Help Net Security

How Open-Source Database immudb Plans to Handle All That Metaverse Data
10 October 2022, Acceleration Economy

immudb (immutable database) 'tamper-proof' database - Open Source Insider
14 December 2021, ComputerWeekly.com

provided by Google News

Share this page