DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Pinot vs. Google Cloud Firestore vs. MarkLogic vs. PlanetScale vs. Spark SQL

System Properties Comparison Apache Pinot vs. Google Cloud Firestore vs. MarkLogic vs. PlanetScale vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMarkLogic  Xexclude from comparisonPlanetScale  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Operational and transactional Enterprise NoSQL databaseScalable, distributed, serverless MySQL database platform built on top of VitessSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score1.49
Rank#155  Overall
#72  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitepinot.apache.orgfirebase.google.com/­products/­firestorewww.progress.com/­marklogicplanetscale.comspark.apache.org/­sql
Technical documentationdocs.pinot.apache.orgfirebase.google.com/­docs/­firestorewww.progress.com/­marklogic/­documentationplanetscale.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsGoogleMarkLogic Corp.PlanetScaleApache Software Foundation
Initial release20152017200120202014
Current release1.0.0, September 202311.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial inforestricted free version is availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++GoScala
Server operating systemsAll OS with a Java JDK11 or higherhostedLinux
OS X
Windows
Docker
Linux
macOS
Linux
OS X
Windows
Data schemeyesschema-freeschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languagenoyes infoSQL92yes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBCAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
Supported programming languagesGo
Java
Python
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes infovia XQuery or JavaScriptyes infoproprietary syntaxno
Triggersyes, with Cloud Functionsyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infocan act as a resource manager in an XA/JTA transactionACID at shard levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Role-based access control at the document and subdocument levelsUsers with fine-grained authorization concept infono user groups or rolesno

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache PinotGoogle Cloud FirestoreMarkLogicPlanetScaleSpark SQL
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

Real-Time Analytics for Mobile App Crashes using Apache Pinot
2 November 2023, Uber

Apache Pinot - SD Times Open Source Project of the Week
31 May 2024, SDTimes.com

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

Google launches Cloud Firestore, a new document database for app developers
3 October 2017, TechCrunch

Google's Cloud-Native NoSQL Database Cloud Firestore Is Now Generally Available
8 February 2019, InfoQ.com

Firestore and Python | NoSQL on Google Cloud
7 August 2020, Towards Data Science

provided by Google News

MarkLogic “The NoSQL Database”. In the MarkLogic Query Console, you can… | by Abhay Srivastava | Apr, 2024
22 April 2024, Medium

Database Platform to Simplify Complex Data | Progress Marklogic
7 February 2023, Progress Software

AI can make logistics data as valuable as intelligence or operational data for mission success
17 April 2024, Breaking Defense

Seven Quick Steps to Setting Up MarkLogic Server in Kubernetes
1 February 2024, release.nl

Intelligence for multi-domain warfighters can now be sourced from logistics operations
13 May 2024, Breaking Defense

provided by Google News

PlanetScale ends free tier bid, sheds staff in profitability bid
11 March 2024, The Register

PlanetScale Ranked Number 188 Fastest-Growing Company in North America on the 2023 Deloitte Technology Fast ...
8 November 2023, businesswire.com

PlanetScale forks MySQL to add vector support
3 October 2023, TechCrunch

PlanetScale Named to Fortune 2023 Best Small Workplaces
31 August 2023, businesswire.com

How to Migrate to PlanetScale's Serverless Database
14 October 2021, The New Stack

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM)
17 March 2024, Yahoo Singapore News

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here