DBMS > HBase vs. JaguarDB vs. Netezza vs. searchxml vs. Snowflake

System Properties Comparison HBase vs. JaguarDB vs. Netezza vs. searchxml vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Performant, highly scalable DBMS for AI and IoT applications

Data warehouse and analytics appliance part of IBM PureSystems

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Wide column store

Key-value store
Vector DBMS

Relational DBMS

Native XML DBMS
Search engine

Relational DBMS

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

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

hbase.apache.org

www.jaguardb.com

www.ibm.com/products/netezza

www.searchxml.net/category/products

www.snowflake.com

Technical documentation

hbase.apache.org/book.html

www.jaguardb.com/support.html

www.searchxml.net/support/handouts

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

DataJaguar, Inc.

IBM

informationpartners gmbh

Snowflake Computing Inc.

Initial release

2008

2015

2000

2015

2014

Current release

2.3.4, January 2021

3.3 July 2023

1.0

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GPL V3.0

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

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux

included in appliance

Windows

hosted

Data scheme

schema-free, schema definition possible

yes

schema-free

yes

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

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

JDBC
ODBC
OLE DB

RESTful HTTP API
WebDAV
XQuery
XSLT

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

C
C++
Fortran
Java
Lua
Perl
Python
R

C++

most other programming languages supported via APIs

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

on the application server

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

Source-replica replication

yes

sychronisation to multiple collections

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

multiple readers, single writer

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

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

rights management via user accounts

Users with fine-grained authorization concept

Domain, group and role-based access control at the document level and for application services

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.