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DBMS > Apache Impala vs. Google Cloud Firestore vs. Kinetica vs. Kingbase vs. YottaDB

System Properties Comparison Apache Impala vs. Google Cloud Firestore vs. Kinetica vs. Kingbase vs. YottaDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparisonKingbase  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopCloud 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.Fully vectorized database across both GPUs and CPUsAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.A fast and solid embedded Key-value store
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
Relational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.45
Rank#262  Overall
#123  Relational DBMS
Score0.20
Rank#317  Overall
#47  Key-value stores
Websiteimpala.apache.orgfirebase.google.com/­products/­firestorewww.kinetica.comwww.kingbase.com.cnyottadb.com
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­firestoredocs.kinetica.comyottadb.com/­resources/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleKineticaBeiJing KINGBASE Information technologies inc.YottaDB, LLC
Initial release20132017201219992001
Current release4.1.0, June 20227.1, August 2021V8.0, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++C and JavaC
Server operating systemsLinuxhostedLinuxLinux
Windows
Docker
Linux
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononoyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsStandard with numerous extensionsby using the Octo plugin
APIs and other access methodsJDBC
ODBC
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, Firebase Rules & Cloud Functionsuser defined functionsuser defined functions
Triggersnoyes, with Cloud Functionsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning (by range, list and hash) and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationSource-replica replicationyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceUsing Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess 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 on table levelfine grained access rights according to SQL-standardUsers and groups based on OS-security mechanisms

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More resources
Apache ImpalaGoogle Cloud FirestoreKineticaKingbaseYottaDB
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