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DBMS > Apache Pinot vs. Atos Standard Common Repository vs. ToroDB vs. Vertica

System Properties Comparison Apache Pinot vs. Atos Standard Common Repository vs. ToroDB vs. Vertica

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonToroDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA MongoDB-compatible JSON document store, built on top of PostgreSQLCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSDocument store
Key-value store
Document storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitepinot.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­torodb/­serverwww.vertica.com
Technical documentationdocs.pinot.apache.orgvertica.com/­documentation
DeveloperApache Software Foundation and contributorsAtos Convergence Creators8KdataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201620162005
Current release1.0.0, September 2023170312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL-V3commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC++
Server operating systemsAll OS with a Java JDK11 or higherLinuxAll OS with a Java 7 VMLinux
Data schemeyesSchema and schema-less with LDAP viewsschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesoptionalyes infostring, integer, double, boolean, date, object_idyes
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.yesnono
Secondary indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languagenoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBCLDAPADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
Python
All languages with LDAP bindingsC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infocell divisionShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesno
User concepts infoAccess controlLDAP bind authenticationAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache PinotAtos Standard Common RepositoryToroDBVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Apache PinotAtos Standard Common RepositoryToroDBVertica infoOpenText™ Vertica™
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