DBMS > Elasticsearch vs. Snowflake vs. SWC-DB vs. Warp 10

System Properties Comparison Elasticsearch vs. Snowflake vs. SWC-DB vs. Warp 10

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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

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

A high performance, scalable Wide Column DBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

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	128.79
Rank	#8	Overall
	#1	Search engines

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

www.elastic.co/elasticsearch

www.snowflake.com

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

www.warp10.io

Technical documentation

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

docs.snowflake.net/manuals/index.html

www.warp10.io/content/02_Getting_started

Developer

Elastic

Snowflake Computing Inc.

Alex Kashirin

SenX

Initial release

2010

2014

2020

2015

Current release

8.6, January 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

GPL V3

Open Source

Apache License 2.0

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++

Java

Server operating systems

All OS with a Java VM

hosted

Linux

Linux
OS X
Windows

Data scheme

schema-free

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

yes

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

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

HTTP API
Jupyter
WebSocket

Supported programming languages

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

JavaScript (Node.js)
Python

C++

Server-side scripts

Stored procedures

yes

user defined functions

yes

WarpScript

Triggers

yes

by using the 'percolation' feature

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

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

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

yes

User concepts

Access control

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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