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DBMS > Apache Impala vs. Postgres-XL vs. TDengine vs. Titan

System Properties Comparison Apache Impala vs. Postgres-XL vs. TDengine vs. Titan

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTDengine  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 HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresTime Series DBMS and big data platformTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSRelational DBMSTime Series DBMSGraph DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteimpala.apache.orgwww.postgres-xl.orggithub.com/­taosdata/­TDengine
tdengine.com
github.com/­thinkaurelius/­titan
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgres-xl.org/­documentationdocs.tdengine.comgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaTDEngine, previously Taos DataAurelius, owned by DataStax
Initial release20132014 infosince 2012, originally named StormDB20192012
Current release4.1.0, June 202210 R1, October 20183.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMozilla public licenseOpen Source infoAGPL V3, also commercial editions availableOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CCJava
Server operating systemsLinuxLinux
macOS
Linux
Windows
Linux
OS X
Unix
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infodistributed, parallel query executionStandard SQL with extensions for time-series applicationsno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsnoyes
Triggersnoyesyes, via alarm monitoringyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardyesUser authentification and security via Rexster Graph Server
More information provided by the system vendor
Apache ImpalaPostgres-XLTDengineTitan
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
Apache ImpalaPostgres-XLTDengineTitan
DB-Engines blog posts

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3 March 2015, Paul Andlinger

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Recent citations in the news

Cloudera creates observability tool to help enterprises manage cloud costs
6 June 2023, SiliconANGLE News

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

provided by Google News

TDengine debuts cloud-based time-series data processing platform for IoT deployments
20 September 2022, SiliconANGLE News

TDengine Brings Open Source Time-Series Database to Kubernetes
19 April 2023, Cloud Native Now

New TDengine Benchmark Results Show Up to 37.0x Higher Query Performance Than InfluxDB and TimescaleDB
28 February 2023, GlobeNewswire

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

provided by Google News

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

Beyond Titan: The Evolution of DataStax's New Graph Database
21 June 2016, Datanami

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

provided by Google News



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