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DBMS > Apache Impala vs. Netezza vs. Titan vs. Yaacomo

System Properties Comparison Apache Impala vs. Netezza vs. Titan vs. Yaacomo

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonTitan  Xexclude from comparisonYaacomo  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.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopData warehouse and analytics appliance part of IBM PureSystemsTitan is a Graph DBMS optimized for distributed clusters.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSGraph DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Websiteimpala.apache.orgwww.ibm.com/­products/­netezzagithub.com/­thinkaurelius/­titanyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBMAurelius, owned by DataStaxQ2WEB GmbH
Initial release2013200020122009
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache license, version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemsLinuxLinux infoincluded in applianceLinux
OS X
Unix
Windows
Android
Linux
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
OLE DB
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Fortran
Java
Lua
Perl
Python
R
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infovia pluggable storage backendshorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infoRelationships in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization conceptUser authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standard

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More resources
Apache ImpalaNetezza infoAlso called PureData System for Analytics by IBMTitanYaacomo
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Recent citations in the 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

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

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

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