DBMS > Derby vs. Machbase Neo vs. Microsoft SQL Server vs. Pinecone

System Properties Comparison Derby vs. Machbase Neo vs. Microsoft SQL Server vs. Pinecone

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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.

TimeSeries DBMS for AIoT and BigData

Microsofts flagship relational DBMS

A managed, cloud-native vector database

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Website

db.apache.org/derby

machbase.com

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

www.pinecone.io

Technical documentation

db.apache.org/derby/manuals/index.html

machbase.com/dbms

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

docs.pinecone.io/docs/overview

Developer

Apache Software Foundation

Machbase

Microsoft

Pinecone Systems, Inc

Initial release

1997

2013

1989

2019

Current release

10.17.1.0, November 2023

V8.0, August 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free test version available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

Linux
Windows

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

yes

SQL-like query language

yes

APIs and other access methods

JDBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

RESTful HTTP API

Supported programming languages

Java

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

Python

Server-side scripts

Stored procedures

Java Stored Procedures

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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