DBMS > DolphinDB vs. Ehcache vs. PouchDB vs. SQLite

System Properties Comparison DolphinDB vs. Ehcache vs. PouchDB vs. SQLite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS
Vector DBMS

Key-value store

Document store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

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

www.ehcache.org/documentation

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

DolphinDB, Inc

Terracotta Inc, owned by Software AG

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2018

2009

2012

2000

Current release

v2.00.4, January 2022

3.10.0, March 2022

7.1.1, June 2019

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2; commercial licenses available

Open Source

Public Domain

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

JavaScript

Server operating systems

Linux
Windows

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

via views

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

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

JCache

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

Java

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

by using Terracotta Server

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Eventual 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

via file-system locks

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

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.