DBMS > Ehcache vs. EsgynDB vs. GreptimeDB vs. RDF4J vs. Teradata

System Properties Comparison Ehcache vs. EsgynDB vs. GreptimeDB vs. RDF4J vs. Teradata

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

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

An open source Time Series DBMS built for increased scalability, high performance and efficiency

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A hybrid cloud data analytics software platform (Teradata Vantage)

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	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

Technical documentation

www.ehcache.org/documentation

docs.greptime.com

rdf4j.org/documentation

docs.teradata.com

Developer

Terracotta Inc, owned by Software AG

Esgyn

Greptime Inc.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Teradata

Initial release

2009

2015

2022

2004

1984

Current release

3.10.0, March 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Java

C++, Java

Rust

Java

Server operating systems

All OS with a Java VM

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Unix
Windows

hosted
Linux

Data scheme

schema-free

yes

schema-free, schema definition possible

yes

RDF Schemas

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.

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

JCache

ADO.NET
JDBC
ODBC

gRPC
HTTP API
JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

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

Supported programming languages

Java

All languages supporting JDBC/ODBC/ADO.Net

C++
Erlang
Go
Java
JavaScript

Java
PHP
Python

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

Server-side scripts

Stored procedures

Java Stored Procedures

Python

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication between multi datacenters

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

in-memory storage is supported as well

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

Simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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

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