DBMS > Apache Impala vs. H2 vs. Microsoft SQL Server vs. Netezza vs. Pinecone

System Properties Comparison Apache Impala vs. H2 vs. Microsoft SQL Server vs. Netezza vs. Pinecone

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

A managed, cloud-native vector database

Primary database model

Relational DBMS

Vector DBMS

Secondary database models

Document store

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Website

impala.apache.org

www.h2database.com

www.microsoft.com/en-us/sql-server

www.ibm.com/products/netezza

www.pinecone.io

Technical documentation

impala.apache.org/impala-docs.html

www.h2database.com/html/main.html

learn.microsoft.com/en-US/sql/sql-server

docs.pinecone.io/docs/overview

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Thomas Mueller

Microsoft

IBM

Pinecone Systems, Inc

Initial release

2013

2005

1989

2000

2019

Current release

4.1.0, June 2022

2.2.220, July 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

Linux

included in appliance

hosted

Data scheme

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Fortran
Java
Lua
Perl
Python
R

Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures and User-Defined Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

With clustering: 2 database servers on different computers operate on identical copies of a database

yes, but depending on the SQL-Server Edition

Source-replica replication

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

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

yes, multi-version concurrency control (MVCC)

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 rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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