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DBMS > Google Cloud Firestore vs. HarperDB vs. QuestDB vs. Spark SQL

System Properties Comparison Google Cloud Firestore vs. HarperDB vs. QuestDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHarperDB  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionCloud 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.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.A high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument storeTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.36
Rank#53  Overall
#9  Document stores
Score0.60
Rank#244  Overall
#38  Document stores
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­firestorewww.harperdb.ioquestdb.iospark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­firestoredocs.harperdb.io/­docsquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleHarperDBQuestDB Technology IncApache Software Foundation
Initial release2017201720142014
Current release3.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsJava (Zero-GC), C++, RustScala
Server operating systemshostedLinux
OS X
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freedynamic schemayes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes
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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLnoSQL-like data manipulation statementsSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.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 infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsCustom Functions infosince release 3.1nono
Triggersyes, with Cloud Functionsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infothe nodes on which a table resides can be definedSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic execution of specific operationsACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infothrough memory mapped filesno
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.Access rights for users and rolesno
More information provided by the system vendor
Google Cloud FirestoreHarperDBQuestDBSpark SQL
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Google Cloud FirestoreHarperDBQuestDBSpark SQL
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