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DBMS > Apache Impala vs. Apache IoTDB vs. Apache Kylin vs. Faircom EDGE vs. Titan

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Apache Kylin vs. Faircom EDGE vs. Titan

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonApache Kylin  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionAnalytic DBMS for HadoopAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSTime Series DBMSRelational DBMSKey-value store
Relational DBMS
Graph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgkylin.apache.orgwww.faircom.com/­products/­faircom-edgegithub.com/­thinkaurelius/­titan
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlkylin.apache.org/­docsdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationApache Software Foundation, originally contributed from eBay IncFairCom CorporationAurelius, owned by DataStax
Initial release20132018201519792012
Current release4.1.0, June 20221.1.0, April 20233.1.0, July 2020V3, October 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaANSI C, C++Java
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)LinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Unix
Windows
Data schemeyesyesyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI Standard SQL Typesyes
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.nononoyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageANSI SQL for queries (using Apache Calcite)yes infoANSI SQL queriesno
APIs and other access methodsJDBC
ODBC
JDBC
Native API
JDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes info.Net, JavaScript, C/C++yes
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning infoCustomizable business rules for partitioningyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoSynchronous and asynchronous realtime replication based on transaction logsyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparkyesnoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infowhen using SQLyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.User authentification and security via Rexster Graph Server

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Apache ImpalaApache IoTDBApache KylinFaircom EDGE infoformerly c-treeEDGETitan
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