DBMS > Elasticsearch vs. JaguarDB vs. Microsoft Azure Table Storage vs. OpenQM vs. Snowflake

System Properties Comparison Elasticsearch vs. JaguarDB vs. Microsoft Azure Table Storage vs. OpenQM vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Performant, highly scalable DBMS for AI and IoT applications

A Wide Column Store for rapid development using massive semi-structured datasets

QpenQM is a high-performance, self-tuning, multi-value DBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Search engine

Key-value store
Vector DBMS

Wide column store

Multivalue DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.elastic.co/elasticsearch

www.jaguardb.com

azure.microsoft.com/en-us/services/storage/tables

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.snowflake.com

Technical documentation

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

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

Developer

Elastic

DataJaguar, Inc.

Microsoft

Rocket Software, originally Martin Phillips

Snowflake Computing Inc.

Initial release

2010

2015

2012

1993

2014

Current release

8.6, January 2023

3.3 July 2023

3.4-12

License

Commercial or Open Source

Open Source

Elastic License

Open Source

GPL V3.0

commercial

Open Source

GPLv2, extended commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

the server part. Clients available in other languages

Server operating systems

All OS with a Java VM

Linux

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

hosted

Data scheme

schema-free

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

yes

schema-free

yes

with some exceptions

yes

support of semi-structured data formats (JSON, XML, Avro)

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
ODBC

RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by using the 'percolation' feature

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

ACID

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

User concepts

Access control

rights management via user accounts

Access rights based on private key authentication or shared access signatures

Access rights can be defined down to the item level

Users with fine-grained authorization concept, user roles and pluggable authentication

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