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DBMS > Apache Kylin vs. atoti vs. Axibase vs. Vertica

System Properties Comparison Apache Kylin vs. atoti vs. Axibase vs. Vertica

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonatoti  Xexclude from comparisonAxibase  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationCloud 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 DBMSObject oriented DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitekylin.apache.orgatoti.ioaxibase.com/­docs/­atsd/­financewww.vertica.com
Technical documentationkylin.apache.org/­docsdocs.atoti.iovertica.com/­documentation
DeveloperApache Software Foundation, originally contributed from eBay IncActiveViamAxibase CorporationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201520132005
Current release3.1.0, July 20201558512.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree versions availablecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercial 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 systemsLinuxLinuxLinux
Data schemeyesyesYes, 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 dateyesyes infoshort, integer, long, float, double, decimal, stringyes
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.nonono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)Multidimensional Expressions (MDX)SQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Proprietary protocol (Network API)
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
PHP
Python
R
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresPythonyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-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 methodsyesnoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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 controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache KylinatotiAxibaseVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Apache KylinatotiAxibaseVertica infoOpenText™ Vertica™
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