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DBMS > Apache Impala vs. Apache IoTDB vs. Hypertable vs. Postgres-XL vs. Titan

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Hypertable vs. Postgres-XL vs. Titan

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHypertable  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTitan  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.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 FlinkAn open source BigTable implementation based on distributed file systems such as HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSTime Series DBMSWide column storeRelational DBMSGraph DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgwww.postgres-xl.orggithub.com/­thinkaurelius/­titan
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgres-xl.org/­documentationgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationHypertable Inc.Aurelius, owned by DataStax
Initial release2013201820092014 infosince 2012, originally named StormDB2012
Current release4.1.0, June 20221.1.0, April 20230.9.8.11, March 201610 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license availableOpen Source infoMozilla public licenseOpen 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++JavaC++CJava
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)Linux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Linux
OS X
Unix
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nonoyes infoXML type, but no XML query functionality
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoyes infodistributed, parallel query executionno
APIs and other access methodsJDBC
ODBC
JDBC
Native API
C++ API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnouser defined functionsyes
Triggersnoyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal 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 replicasselectable replication factor on file system levelyes
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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyesnofine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Server

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More resources
Apache ImpalaApache IoTDBHypertablePostgres-XLTitan
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