DBMS > Elasticsearch vs. Newts vs. Quasardb vs. Snowflake

System Properties Comparison Elasticsearch vs. Newts vs. Quasardb vs. Snowflake

Please select another system to include it in the comparison.

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

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

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

Primary database model

Search engine

Time Series 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	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.elastic.co/elasticsearch

opennms.github.io/newts

quasar.ai

www.snowflake.com

Technical documentation

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

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

docs.snowflake.net/manuals/index.html

Developer

Elastic

OpenNMS Group

quasardb

Snowflake Computing Inc.

Initial release

2010

2014

2009

2014

Current release

8.6, January 2023

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

BSD
Linux
OS X
Windows

hosted

Data scheme

schema-free

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

schema-free

yes

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

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

HTTP REST
Java API

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

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

Java

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by using the 'percolation' feature

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

consistent hashing

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

with Hadoop integration

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

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

by using LevelDB

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

Transient mode

User concepts

Access control

Cryptographically strong user authentication and audit trail

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

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.