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DBMS > Google Cloud Firestore vs. HarperDB vs. Hypertable vs. RavenDB vs. Spark SQL

System Properties Comparison Google Cloud Firestore vs. HarperDB vs. Hypertable vs. RavenDB vs. Spark SQL

Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHarperDB  Xexclude from comparisonHypertable  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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.An open source BigTable implementation based on distributed file systems such as HadoopOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument storeWide column storeDocument storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score0.55
Rank#248  Overall
#38  Document stores
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­firestorewww.harperdb.ioravendb.netspark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­firestoredocs.harperdb.io/­docsravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleHarperDBHypertable Inc.Hibernating RhinosApache Software Foundation
Initial release20172017200920102014
Current release3.1, August 20210.9.8.11, March 20165.4, July 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoGNU version 3. Commercial license availableOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsC++C#Scala
Server operating systemshostedLinux
OS X
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Data schemeschema-freedynamic schemaschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesnonoyes
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.nonono
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyesno
SQL infoSupport of SQLnoSQL-like data manipulation statementsnoSQL-like query language (RQL)SQL-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
C++ API
Thrift
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
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++
Java
Perl
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsCustom Functions infosince release 3.1noyesno
Triggersyes, with Cloud Functionsnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infothe nodes on which a table resides can be definedselectable replication factor on file system levelMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic execution of specific operationsnoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
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 rolesnoAuthorization levels configured per client per databaseno

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More resources
Google Cloud FirestoreHarperDBHypertableRavenDBSpark SQL
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