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DBMS > Apache Impala vs. FatDB vs. Google Cloud Firestore vs. HarperDB

System Properties Comparison Apache Impala vs. FatDB vs. Google Cloud Firestore vs. HarperDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHarperDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAnalytic DBMS for HadoopA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cloud 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.
Primary database modelRelational DBMSDocument store
Key-value store
Document storeDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score0.60
Rank#244  Overall
#38  Document stores
Websiteimpala.apache.orgfirebase.google.com/­products/­firestorewww.harperdb.io
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­firestoredocs.harperdb.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFatCloudGoogleHarperDB
Initial release2013201220172017
Current release4.1.0, June 20223.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercial infofree community edition available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#Node.js
Server operating systemsLinuxWindowshostedLinux
OS X
Data schemeyesschema-freeschema-freedynamic schema
Typing infopredefined data types such as float or dateyesyesyesyes infoJSON data types
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsno infoVia inetgration in SQL ServernoSQL-like data manipulation statements
APIs and other access methodsJDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCC#Go
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
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infovia applicationsyes, Firebase Rules & Cloud FunctionsCustom Functions infosince release 3.1
Triggersnoyes infovia applicationsyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorMulti-source replicationyes infothe nodes on which a table resides can be defined
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno infoCan implement custom security layer via applicationsAccess 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 roles

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More resources
Apache ImpalaFatDBGoogle Cloud FirestoreHarperDB
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