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DBMS > Apache Kylin vs. Datomic vs. RocksDB vs. Vertica

System Properties Comparison Apache Kylin vs. Datomic vs. RocksDB vs. Vertica

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonDatomic  Xexclude from comparisonRocksDB  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 stackDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEmbeddable persistent key-value store optimized for fast storage (flash and RAM)Cloud 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 DBMSRelational DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.14
Rank#171  Overall
#77  Relational DBMS
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score2.84
Rank#97  Overall
#16  Key-value stores
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitekylin.apache.orgwww.datomic.comrocksdb.orgwww.vertica.com
Technical documentationkylin.apache.org/­docsdocs.datomic.comgithub.com/­facebook/­rocksdb/­wikivertica.com/­documentation
DeveloperApache Software Foundation, originally contributed from eBay IncCognitectFacebook, Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201220132005
Current release3.1.0, July 20201.0.7180, July 20249.4.0, June 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infoBSDcommercial 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 languageJavaJava, ClojureC++C++
Server operating systemsLinuxAll OS with a Java VMLinuxLinux
Data schemeyesyesschema-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 dateyesyesnoyes
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.nononono
Secondary indexesyesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)nonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIC++ API
Java API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
C
C++
Go
Java
Perl
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peershorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesMulti-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 methodsyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Apache KylinDatomicRocksDBVertica infoOpenText™ Vertica™
Recent citations in the news

Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

eBay’s Kylin Becomes a Top-Level Apache Open Source Project
9 December 2015, eBay Inc.

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MapR Hadoop Upgrade Spins YARN, Supports HP Vertica Analytics Platform
31 May 2024, Data Center Knowledge

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