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DBMS > Apache Impala vs. Google Cloud Datastore vs. Hypertable vs. SiteWhere

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. Hypertable vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonSiteWhere  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSDocument storeWide column storeTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websiteimpala.apache.orgcloud.google.com/­datastoregithub.com/­sitewhere/­sitewhere
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docssitewhere1.sitewhere.io/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleHypertable Inc.SiteWhere
Initial release2013200820092010
Current release4.1.0, June 20220.9.8.11, March 2016
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Java
Server operating systemsLinuxhostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Windows
Data schemeyesschema-freeschema-freepredefined scheme
Typing infopredefined data types such as float or dateyesyes, details herenoyes
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 indexesyesyesrestricted infoonly exact value or prefix value scansno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)nono
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
HTTP REST
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App Engineno
TriggersnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosselectable replication factor on file system levelselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonono
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)noUsers with fine-grained authorization concept

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More resources
Apache ImpalaGoogle Cloud DatastoreHypertableSiteWhere
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