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DBMS > Apache Impala vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. XTDB

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. XTDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Wide Column Store for rapid development using massive semi-structured datasetsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSDocument storeWide column storeDocument 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
Score4.47
Rank#76  Overall
#12  Document stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.11
Rank#343  Overall
#46  Document stores
Websiteimpala.apache.orgcloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docswww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoftJuxt Ltd.
Initial release2013200820122019
Current release4.1.0, June 20221.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Clojure
Server operating systemsLinuxhostedhostedAll OS with a Java 8 (and higher) VM
Linux
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyes, extensible-data-notation format
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)nolimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App Enginenono
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownono
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 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 Transactionsoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
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)Access rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaGoogle Cloud DatastoreMicrosoft Azure Table StorageXTDB infoformerly named Crux
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