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DBMS > Apache Doris vs. Apache Pinot vs. DuckDB vs. Google Cloud Datastore vs. Teradata Aster

System Properties Comparison Apache Doris vs. Apache Pinot vs. DuckDB vs. Google Cloud Datastore vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonApache Pinot  Xexclude from comparisonDuckDB  Xexclude from comparisonGoogle Cloud Datastore  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.
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyAn embeddable, in-process, column-oriented SQL OLAP RDBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#235  Overall
#110  Relational DBMS
Score0.35
Rank#274  Overall
#128  Relational DBMS
Score5.61
Rank#60  Overall
#34  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Websitedoris.apache.org
github.com/­apache/­doris
pinot.apache.orgduckdb.orgcloud.google.com/­datastore
Technical documentationgithub.com/­apache/­doris/­wikidocs.pinot.apache.orgduckdb.org/­docscloud.google.com/­datastore/­docs
DeveloperApache Software Foundation, originally contributed from BaiduApache Software Foundation and contributorsGoogleTeradata
Initial release20172015201820082005
Current release1.2.2, February 20231.0.0, September 20231.0.0, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoMIT Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsLinuxAll OS with a Java JDK11 or higherserver-lesshostedLinux
Data schemeyesyesyesschema-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 dateyesyesyesyes, details hereyes
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 infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query languageyesSQL-like query language (GQL)yes
APIs and other access methodsJDBC
MySQL client
JDBCArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesJavaGo
Java
Python
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functionsnousing Google App EngineR packages
TriggersnonoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioningnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication using Paxosyes 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 methodsnonoyes infousing Google Cloud Dataflowyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache DorisApache PinotDuckDBGoogle Cloud DatastoreTeradata Aster
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Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

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Teradata Integrates Big Data Analytic Architecture
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