DBMS > Apache Phoenix vs. Elasticsearch vs. Sequoiadb vs. Snowflake

System Properties Comparison Apache Phoenix vs. Elasticsearch vs. Sequoiadb vs. Snowflake

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

NewSQL database with distributed OLTP and SQL

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

Primary database model

Relational DBMS

Search engine

Document store
Relational 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	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

phoenix.apache.org

www.elastic.co/elasticsearch

www.sequoiadb.com

www.snowflake.com

Technical documentation

phoenix.apache.org

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

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Elastic

Sequoiadb Ltd.

Snowflake Computing Inc.

Initial release

2014

2010

2013

2014

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

8.6, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Elastic License

Open Source

Server: AGPL; Client: Apache V2

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

Linux
Unix
Windows

All OS with a Java VM

Linux

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

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

oid, date, timestamp, binary, regex

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

yes

SQL-like query language

yes

APIs and other access methods

JDBC

Java API
RESTful HTTP/JSON API

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

.Net
C++
Java
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

JavaScript

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

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

ACID

Document is locked during a transaction

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.

yes

Memcached and Redis integration

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

simple password-based access control

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.