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DBMS > Apache Impala vs. Apache Kylin vs. Google Cloud Datastore vs. TerarkDB vs. TimesTen

System Properties Comparison Apache Impala vs. Apache Kylin vs. Google Cloud Datastore vs. TerarkDB vs. TimesTen

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTerarkDB  Xexclude from comparisonTimesTen  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 key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value storeRelational DBMS
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
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websiteimpala.apache.orgkylin.apache.orgcloud.google.com/­datastoregithub.com/­bytedance/­terarkdbwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docscloud.google.com/­datastore/­docsbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcdocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncGoogleByteDance, originally TerarkOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20132015200820161998
Current release4.1.0, June 20223.1.0, July 202011 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercial inforestricted open source version availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++
Server operating systemsLinuxLinuxhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, 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.nonononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)SQL-like query language (GQL)noyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Java API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App EnginenoPL/SQL
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using PaxosnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infousing Google Cloud Dataflownono
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.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesyes
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)nofine grained access rights according to SQL-standard

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More resources
Apache ImpalaApache KylinGoogle Cloud DatastoreTerarkDBTimesTen
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