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DBMS > Apache Impala vs. Apache Pinot vs. Google Cloud Bigtable vs. Oracle Berkeley DB

System Properties Comparison Apache Impala vs. Apache Pinot vs. Google Cloud Bigtable vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Pinot  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Widely used in-process key-value store
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Key-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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websiteimpala.apache.orgpinot.apache.orgcloud.google.com/­bigtablewww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationimpala.apache.org/­impala-docs.htmldocs.pinot.apache.orgcloud.google.com/­bigtable/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation and contributorsGoogleOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2013201520151994
Current release4.1.0, June 20221.0.0, September 202318.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen 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 languageC++JavaC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinuxAll OS with a Java JDK11 or higherhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.nonoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
ODBC
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
.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 proceduresyes infouser defined functions and integration of map-reducenono
Triggersnonoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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)no

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More resources
Apache ImpalaApache PinotGoogle Cloud BigtableOracle Berkeley DB
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