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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSKey-value storeKey-value store
Wide column store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score11.30
Rank#41  Overall
#25  Relational DBMS
Score0.16
Rank#321  Overall
#47  Key-value stores
Score2.70
Rank#96  Overall
#15  Key-value stores
#7  Wide column stores
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgercloud.google.com/­bigtable
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­bigtable/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsGoogle
Initial release201320172015
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Go
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
hosted
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnono
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 indexesyesnono
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/ODBCGoC#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonono
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 (IAM)

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More resources
Apache ImpalaBadgerGoogle Cloud Bigtable
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