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DBMS > Apache Doris vs. Apache Impala vs. Google Cloud Datastore vs. Oracle Berkeley DB

System Properties Comparison Apache Doris vs. Apache Impala vs. Google Cloud Datastore vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used in-process key-value store
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitedoris.apache.org
github.com/­apache/­doris
impala.apache.orgcloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationgithub.com/­apache/­doris/­wikiimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperApache Software Foundation, originally contributed from BaiduApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2017201320081994
Current release1.2.2, February 20234.1.0, June 202218.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2commercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinuxLinuxhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereno
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.nononoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language (GQL)yes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesJavaAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reduceusing Google App Engineno
TriggersnonoCallbacks using the Google Apps Engineyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 integritynonoyes infovia ReferenceProperties or Ancestor pathsno
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 datayesyesyes
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.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess 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)no

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More resources
Apache DorisApache ImpalaGoogle Cloud DatastoreOracle Berkeley DB
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