DBMS > DolphinDB vs. Elasticsearch vs. KeyDB

System Properties Comparison DolphinDB vs. Elasticsearch vs. KeyDB

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS for big data, integrated with a lightweight distributed computing framework and a vector programming language

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Primary database model

Time Series DBMS

Search engine

Key-value store

Secondary database models

Document store

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

Score	0.74
Rank	#198	Overall
	#12	Time Series DBMS

Score	151.25
Rank	#8	Overall
	#1	Search engines

Score	0.21
Rank	#277	Overall
	#42	Key-value stores

Website

www.dolphindb.com

www.elastic.co/elasticsearch

github.com/JohnSully/KeyDB
keydb.dev

Technical documentation

www.dolphindb.com/help

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.keydb.dev/docs/intro

Developer

DolphinDB, Inc

Elastic

EQ Alpha Technology Ltd.

Initial release

2018

2010

2019

Current release

7.8.0, June 2020

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2; Elastic License

Open Source

BSD-3

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.

Elasticsearch Service on Elastic Cloud: Try out the official hosted Elasticsearch and Kibana offering available on Amazon Web Services, Google Cloud and Microsoft Azure that's powered by the creators of Elasticsearch.

Implementation language

C++

Java

C++

Server operating systems

Linux
Windows

All OS with a Java VM

Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

All search fields are automatically indexed

yes

by using the Redis Search module

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

C#
C++
Java
JavaScript
Python
R

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

Lua

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

Transaction concepts

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

yes

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Memcached and Redis integration

yes

User concepts

Access control

Administrators, Users, Groups

simple password-based access control and ACL

More information provided by the system vendor

Specific characteristics

Elasticsearch is an open source search and analytics engine. As the heart of the...
» more

Competitive advantages

Open source Real-time indexsearch, and analysis Horizontally scalable Distributed...
» more

Typical application scenarios

Enterprise search (search experiences for your workplace, apps, and websites), observability...
» more

Key customers

Thousands of organizations worldwide, including Cisco, eBay, Goldman Sachs, Microsoft,...
» more

Market metrics

Public as of October 2018 Distributed workforce with 1900+ employees around the globe...
» more

Licensing and pricing models

The Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash) is free and open source...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.