DBMS > Axibase vs. Elasticsearch vs. openGemini vs. SWC-DB

System Properties Comparison Axibase vs. Elasticsearch vs. openGemini vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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 open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Time Series DBMS

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	128.79
Rank	#8	Overall
	#1	Search engines

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

axibase.com/docs/atsd/finance

www.elastic.co/elasticsearch

www.opengemini.org
github.com/openGemini

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

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

docs.opengemini.org/guide

Developer

Axibase Corporation

Elastic

Huawei and openGemini community

Alex Kashirin

Initial release

2013

2010

2022

2020

Current release

15585

8.6, January 2023

1.1, July 2023

0.5, April 2021

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Elastic License

Open Source

Apache Version 2.0

Open Source

GPL V3

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++

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

Linux

Data scheme

yes

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

short, integer, long, float, double, decimal, string

yes

Integer, Float, Boolean, String

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

SQL-like query language

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Java API
RESTful HTTP/JSON API

HTTP REST

Proprietary protocol
Thrift

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

C++

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

User concepts

Access control

Administrators and common users accounts

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More resources

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2 March 2016, Paul Andlinger

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