DBMS > Apache Impala vs. InfinityDB vs. JaguarDB vs. Netezza vs. Snowflake

System Properties Comparison Apache Impala vs. InfinityDB vs. JaguarDB vs. Netezza vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A Java embedded Key-Value Store which extends the Java Map interface

Performant, highly scalable DBMS for AI and IoT applications

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

Relational DBMS

Key-value store

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Document store

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

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

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

impala.apache.org

boilerbay.com

www.jaguardb.com

www.ibm.com/products/netezza

www.snowflake.com

Technical documentation

impala.apache.org/impala-docs.html

boilerbay.com/infinitydb/manual

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Boiler Bay Inc.

DataJaguar, Inc.

IBM

Snowflake Computing Inc.

Initial release

2013

2002

2015

2000

2014

Current release

4.1.0, June 2022

4.0

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

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

C++

Java

C++

the server part. Clients available in other languages

Server operating systems

Linux

All OS with a Java VM

Linux

included in appliance

hosted

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

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

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

JDBC
ODBC

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Java

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

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

rights management via user accounts

Users with fine-grained authorization concept

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

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