DBMS > MySQL vs. Pinecone vs. QuestDB vs. SAP SQL Anywhere vs. Sphinx

System Properties Comparison MySQL vs. Pinecone vs. QuestDB vs. SAP SQL Anywhere vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

A managed, cloud-native vector database

A high performance open source SQL database for time series data

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

www.mysql.com

www.pinecone.io

questdb.io

www.sap.com/products/technology-platform/sql-anywhere.html

sphinxsearch.com

Technical documentation

dev.mysql.com/doc

docs.pinecone.io/docs/overview

questdb.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

sphinxsearch.com/docs

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Pinecone Systems, Inc

QuestDB Technology Inc

SAP

formerly Sybase

Sphinx Technologies Inc.

Initial release

1995

2019

2014

1992

2001

Current release

9.0.0, July 2024

17, July 2015

3.5.1, February 2023

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

commercial

Open Source

GPL version 2, commercial licence available

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 and C++

Java (Zero-GC), C++, Rust

C++

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

full-text index on all search fields

SQL

Support of SQL

yes

with proprietary extensions

SQL with time-series extensions

yes

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Python

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

proprietary syntax

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning (by timestamps)

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication with eventual consistency

Source-replica replication

Database mirroring

none

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

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID for single-table writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

through memory mapped files

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

Combine Java and Rust Code Coverage in a Polyglot Project
10 September 2024

Building a new vector based storage model
22 August 2024

Calibrating VWAP executions with QuestDB and Grafana
16 August 2024

The story of our SAMPLE BY enhancements
7 August 2024

A cloud engineer's first QuestDB Pull Request
5 August 2024

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.