DBMS > GeoMesa vs. Realm vs. Teradata vs. Tkrzw

System Properties Comparison GeoMesa vs. Realm vs. Teradata vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A hybrid cloud data analytics software platform (Teradata Vantage)

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

Technical documentation

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

realm.io/docs

docs.teradata.com

Developer

CCRi and others

Realm, acquired by MongoDB in May 2019

Teradata

Mikio Hirabayashi

Initial release

2014

1984

2020

Current release

4.0.5, February 2024

Teradata Vantage 1.0 MU2, January 2019

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

commercial

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

Scala

C++

Server operating systems

Android
Backend: server-less
iOS
Windows

hosted
Linux

Linux
macOS

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

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

depending on storage layer

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.

depending on storage layer

yes

In-Memory realm

yes

using specific database classes

User concepts

Access control

yes

depending on the DBMS used for storage

yes

fine grained access rights according to SQL-standard

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