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

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

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionRealtime 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 storePlatform for big data analytics on multistructured data sources and types
Primary database modelRelational 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Websitepinot.apache.orgcloud.google.com/­bigtablewww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.pinot.apache.orgcloud.google.com/­bigtable/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperApache Software Foundation and contributorsGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleTeradata
Initial release2015201519942005
Current release1.0.0, September 202318.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infocommercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsAll OS with a Java JDK11 or higherhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Data schemeyesschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesnonoyes
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.noyes infoonly with the Berkeley DB XML editionyes infoin Aster File Store
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoyes infoSQL interfaced based on SQLite is availableyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
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
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoR packages
Triggersnoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACID
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.noyesno
User concepts infoAccess controlAccess 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 PinotGoogle Cloud BigtableOracle Berkeley DBTeradata Aster
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