DBMS > Apache Doris vs. Elasticsearch vs. Machbase Neo vs. SwayDB

System Properties Comparison Apache Doris vs. Elasticsearch vs. Machbase Neo vs. SwayDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

TimeSeries DBMS for AIoT and BigData

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

doris.apache.org
github.com/apache/doris

www.elastic.co/elasticsearch

machbase.com

swaydb.simer.au

Technical documentation

github.com/apache/doris/wiki

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

machbase.com/dbms

Developer

Apache Software Foundation, originally contributed from Baidu

Elastic

Machbase

Simer Plaha

Initial release

2017

2010

2013

2018

Current release

1.2.2, February 2023

8.6, January 2023

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Elastic License

commercial

free test version available

Open Source

GNU Affero GPL V3.0

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

Java

Scala

Server operating systems

Linux

All OS with a Java VM

Linux
macOS
Windows

Data scheme

yes

schema-free

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

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
MySQL client

Java API
RESTful HTTP/JSON API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

Java

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of operations

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.

Memcached and Redis integration

yes

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

Workload Isolation in Apache Doris: Optimizing Resource Management and Performance
25 May 2024, hackernoon.com

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Using Arrow Flight SQL Protocol in Apache Doris 2.1 For Super Fast Data Transfer
8 May 2024, hackernoon.com

provided by Google News

8 Powerful Alternatives to Elasticsearch
25 April 2024, Yahoo Finance

Splunk vs Elasticsearch | A Comparison and How to Choose
12 January 2024, SentinelOne

Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently
29 April 2024, InfoQ.com

Introducing Elasticsearch Vector Database to Azure OpenAI Service On Your Data (Preview)
26 March 2024, GovTech

Elasticsearch Open Inference API Supports Cohere Rerank 3
11 April 2024, Business Wire

provided by Google News

Share this page