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DBMS > Apache Impala vs. Apache Kylin vs. HugeGraph vs. Tarantool

System Properties Comparison Apache Impala vs. Apache Kylin vs. HugeGraph vs. Tarantool

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonHugeGraph  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackA fast-speed and highly-scalable Graph DBMSIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMSGraph DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteimpala.apache.orgkylin.apache.orggithub.com/­hugegraph
hugegraph.apache.org
www.tarantool.io
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docshugegraph.apache.org/­docswww.tarantool.io/­en/­doc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncBaiduVK
Initial release2013201520182008
Current release4.1.0, June 20223.1.0, July 20200.92.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaC and C++
Server operating systemsLinuxLinuxLinux
macOS
Unix
BSD
Linux
macOS
Data schemeyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)noFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
Open binary protocol
Supported programming languagesAll languages supporting JDBC/ODBCGroovy
Java
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsLua, C and SQL stored procedures
Triggersnonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesvia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual 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
Foreign keys infoReferential integritynoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers, roles and permissionsAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
Apache ImpalaApache KylinHugeGraphTarantool
DB-Engines blog posts

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

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Recent citations in the news

Apache Impala becomes Top-Level Project
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Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

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

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