DBMS > H2 vs. HarperDB vs. Microsoft SQL Server vs. Netezza vs. Pinecone

System Properties Comparison H2 vs. HarperDB vs. Microsoft SQL Server vs. Netezza vs. Pinecone

Editorial information provided by DB-Engines

Name

Description

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

A managed, cloud-native vector database

Primary database model

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

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

www.h2database.com

www.harperdb.io

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

www.ibm.com/products/netezza

www.pinecone.io

Technical documentation

www.h2database.com/html/main.html

docs.harperdb.io/docs

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

docs.pinecone.io/docs/overview

Developer

Thomas Mueller

HarperDB

Microsoft

IBM

Pinecone Systems, Inc

Initial release

2005

2017

1989

2000

2019

Current release

2.2.220, July 2023

3.1, August 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

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

commercial

free community edition available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Node.js

C++

Server operating systems

All OS with a Java VM

Linux
OS X

Linux
Windows

Linux

included in appliance

hosted

Data scheme

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

yes

SQL-like data manipulation statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

Java

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Java Stored Procedures and User-Defined Functions

Custom Functions

since release 3.1

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

none

A table resides as a whole on one (or more) nodes in a cluster

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

the nodes on which a table resides can be defined

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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