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DBMS > Apache Impala vs. Google Cloud Bigtable vs. Realm

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. Realm

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSKey-value store
Wide column store
Document 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score7.60
Rank#52  Overall
#9  Document stores
Websiteimpala.apache.orgcloud.google.com/­bigtablerealm.io
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsrealm.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleRealm, acquired by MongoDB in May 2019
Initial release201320152014
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemsLinuxhostedAndroid
Backend: server-less
iOS
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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 indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono inforuns within the applications so server-side scripts are unnecessary
Triggersnonoyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoIn-Memory realm
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 (IAM)yes

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More resources
Apache ImpalaGoogle Cloud BigtableRealm
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