DBMS > Cachelot.io vs. DolphinDB vs. Ehcache vs. PostGIS

System Properties Comparison Cachelot.io vs. DolphinDB vs. Ehcache vs. PostGIS

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A widely adopted Java cache with tiered storage options

Spatial extension of PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

Technical documentation

docs.dolphindb.cn/en/help200/index.html

www.ehcache.org/documentation

postgis.net/documentation

Developer

DolphinDB, Inc

Terracotta Inc, owned by Software AG

Initial release

2015

2018

2009

2005

Current release

v2.00.4, January 2022

3.10.0, March 2022

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

free community version available

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL v2.0

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

C++

Java

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

All OS with a Java VM

Data scheme

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Memcached protocol

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JCache

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

by using Terracotta Server

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

Administrators, Users, Groups

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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