DBMS > BigObject vs. EsgynDB vs. GeoMesa vs. ITTIA

System Properties Comparison BigObject vs. EsgynDB vs. GeoMesa vs. ITTIA

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

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

Edge Time Series DBMS with Real-Time Stream Processing

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Spatial DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Website

Technical documentation

docs.bigobject.io

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

Developer

BigObject, Inc.

Esgyn

CCRi and others

ITTIA L.L.C.

Initial release

2015

2014

2007

Current release

5.0.0, May 2024

8.7

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Apache License 2.0

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

C++, Java

Scala

C and C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Linux
Windows

Data scheme

yes

Fixed schema

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C++
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

depending on storage layer

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

depending on storage layer

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

depending on storage layer

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

yes, multi-version concurrency control (MVCC)

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

depending on storage layer

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

Database file passwords

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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