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DBMS > Apache Impala vs. Apache Kylin vs. Google Cloud Datastore vs. OrigoDB

System Properties Comparison Apache Impala vs. Apache Kylin vs. Google Cloud Datastore vs. OrigoDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fully ACID in-memory object graph database
Primary database modelRelational DBMSRelational DBMSDocument storeDocument store
Object oriented DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.14
Rank#171  Overall
#77  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.00
Rank#385  Overall
#54  Document stores
#21  Object oriented DBMS
Websiteimpala.apache.orgkylin.apache.orgcloud.google.com/­datastoreorigodb.com
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docscloud.google.com/­datastore/­docsorigodb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncGoogleRobert Friberg et al
Initial release2013201520082009 infounder the name LiveDB
Current release4.1.0, June 20223.1.0, July 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC#
Server operating systemsLinuxLinuxhostedLinux
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereUser defined using .NET types and collections
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 infocan be achieved using .NET
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)SQL-like query language (GQL)no
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
HTTP API
LINQ
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App Engineyes
TriggersnoCallbacks using the Google Apps Engineyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsdepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
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)Role based authorization

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More resources
Apache ImpalaApache KylinGoogle Cloud DatastoreOrigoDB
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