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DBMS > Apache Impala vs. Google Cloud Bigtable vs. H2GIS vs. Riak KV

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. H2GIS vs. Riak KV

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonH2GIS  Xexclude from comparisonRiak KV  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.Spatial extension of H2Distributed, fault tolerant key-value store
Primary database modelRelational DBMSKey-value store
Wide column store
Spatial DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score0.05
Rank#372  Overall
#7  Spatial DBMS
Score4.44
Rank#80  Overall
#9  Key-value stores
Websiteimpala.apache.orgcloud.google.com/­bigtablewww.h2gis.org
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docswww.h2gis.org/­docs/­homewww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleCNRSOpenSource, formerly Basho Technologies
Initial release2013201520132009
Current release4.1.0, June 20223.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoLGPL 3.0Open Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaErlang
Server operating systemsLinuxhostedLinux
OS X
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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.nononono
Secondary indexesyesnoyesrestricted
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infobased on H2Erlang
Triggersnonoyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesyes infobased on H2selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoyes
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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 infobased on H2yes, using Riak Security

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More resources
Apache ImpalaGoogle Cloud BigtableH2GISRiak KV
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