DBMS > Hypertable vs. Ignite vs. Microsoft Azure AI Search vs. PouchDB vs. Snowflake

System Properties Comparison Hypertable vs. Ignite vs. Microsoft Azure AI Search vs. PouchDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Search-as-a-service for web and mobile app development

JavaScript DBMS with an API inspired by CouchDB

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

Primary database model

Wide column store

Key-value store
Relational DBMS

Search engine

Document store

Relational DBMS

Secondary database models

Vector DBMS

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

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

ignite.apache.org

azure.microsoft.com/en-us/services/search

pouchdb.com

www.snowflake.com

Technical documentation

apacheignite.readme.io/docs

learn.microsoft.com/en-us/azure/search

pouchdb.com/guides

docs.snowflake.net/manuals/index.html

Developer

Hypertable Inc.

Apache Software Foundation

Microsoft

Apache Software Foundation

Snowflake Computing Inc.

Initial release

2009

2015

2012

2014

Current release

0.9.8.11, March 2016

Apache Ignite 2.6

7.1.1, June 2019

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

commercial

Open Source

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

C++

C++, Java, .Net

JavaScript

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Solaris
Windows

hosted

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Data scheme

schema-free

yes

schema-free

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

restricted

only exact value or prefix value scans

yes

via views

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

C++ API
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Python

JavaScript

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

View functions in JavaScript

user defined functions

Triggers

yes (cache interceptors and events)

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes (replicated cache)

yes

Implicit feature of the cloud service

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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 IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Security Hooks for custom implementations

yes

using Azure authentication

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.