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DBMS > Apache Kylin vs. Tarantool vs. YugabyteDB

System Properties Comparison Apache Kylin vs. Tarantool vs. YugabyteDB

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonTarantool  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extensionDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitekylin.apache.orgwww.tarantool.iowww.yugabyte.com
Technical documentationkylin.apache.org/­docswww.tarantool.io/­en/­docdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperApache Software Foundation, originally contributed from eBay IncVKYugabyte Inc.
Initial release201520082017
Current release3.1.0, July 20202.10.0, May 20222.19, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageJavaC and C++C and C++
Server operating systemsLinuxBSD
Linux
macOS
Linux
OS X
Data schemeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsdepending on used data model
Typing infopredefined data types such as float or dateyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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 indexesyesyesyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)Full-featured ANSI SQL supportyes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Open binary protocolJDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesC
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresLua, C and SQL stored proceduresyes infosql, plpgsql, C
Triggersyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Hash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyes, write ahead loggingyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
yes
More information provided by the system vendor
Apache KylinTarantoolYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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Apache KylinTarantoolYugabyteDB
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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