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DBMS > Apache Drill vs. Apache Impala vs. Bangdb vs. Netezza

System Properties Comparison Apache Drill vs. Apache Impala vs. Bangdb vs. Netezza

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonApache Impala  Xexclude from comparisonBangdb  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageAnalytic DBMS for HadoopConverged and high performance database for device data, events, time series, document and graphData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument store
Graph DBMS
Time Series DBMS
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitedrill.apache.orgimpala.apache.orgbangdb.comwww.ibm.com/­products/­netezza
Technical documentationdrill.apache.org/­docsimpala.apache.org/­impala-docs.htmldocs.bangdb.com
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by ClouderaSachin Sinha, BangDBIBM
Initial release2012201320122000
Current release1.20.3, January 20234.1.0, June 2022BangDB 2.0, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2Open Source infoBSD 3commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++
Server operating systemsLinux
OS X
Windows
LinuxLinuxLinux infoincluded in appliance
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes: string, long, double, int, geospatial, stream, eventsyes
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.nonono
Secondary indexesnoyesyes infosecondary, composite, nested, reverse, geospatialyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like DML and DDL statementsSQL like support with command line toolyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languagesC++All languages supporting JDBC/ODBCC
C#
C++
Java
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reducenoyes
Triggersnonoyes, Notifications (with Streaming only)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor, Knob for CAP (enterprise version only)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyTunable consistency, set CAP knob accordingly
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, optimistic concurrency controlyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyes, implements WAL (Write ahead log) as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenoyes, run db with in-memory only mode
User concepts infoAccess controlDepending on the underlying data sourceAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes (enterprise version only)Users with fine-grained authorization concept

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More resources
Apache DrillApache ImpalaBangdbNetezza infoAlso called PureData System for Analytics by IBM
Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

provided by Google News

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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

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



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