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DBMS > Apache Impala vs. Datomic vs. Google Cloud Firestore

System Properties Comparison Apache Impala vs. Datomic vs. Google Cloud Firestore

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud 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.
Primary database modelRelational DBMSRelational DBMSDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Websiteimpala.apache.orgwww.datomic.comfirebase.google.com/­products/­firestore
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comfirebase.google.com/­docs/­firestore
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectGoogle
Initial release201320122017
Current release4.1.0, June 20221.0.6735, June 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, Clojure
Server operating systemsLinuxAll OS with a Java VMhosted
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyes, Firebase Rules & Cloud Functions
TriggersnoBy using transaction functionsyes, with Cloud Functions
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoUsing Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and development
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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More resources
Apache ImpalaDatomicGoogle Cloud Firestore
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