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DBMS > Netezza vs. QuestDB vs. Sadas Engine vs. XTDB

System Properties Comparison Netezza vs. QuestDB vs. Sadas Engine vs. XTDB

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQuestDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsA high performance open source SQL database for time series dataSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSTime Series DBMSRelational DBMSDocument store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score2.48
Rank#115  Overall
#9  Time Series DBMS
Score0.03
Rank#379  Overall
#156  Relational DBMS
Score0.09
Rank#351  Overall
#47  Document stores
Websitewww.ibm.com/­products/­netezzaquestdb.iowww.sadasengine.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationquestdb.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationwww.xtdb.com/­docs
DeveloperIBMQuestDB Technology IncSADAS s.r.l.Juxt Ltd.
Initial release2000201420062019
Current release8.01.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree trial version availableOpen Source infoMIT License
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 languageJava (Zero-GC), C++, RustC++Clojure
Server operating systemsLinux infoincluded in applianceLinux
macOS
Windows
AIX
Linux
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyes infoschema-free via InfluxDB Line Protocolyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, extensible-data-notation format
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 indexesyesnoyesyes
SQL infoSupport of SQLyesSQL with time-series extensionsyeslimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Proprietary protocol
HTTP REST
JDBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
C
C#
C++
Groovy
Java
PHP
Python
Clojure
Java
Server-side scripts infoStored proceduresyesnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with eventual consistencynoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID for single-table writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infothrough memory mapped filesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Netezza infoAlso called PureData System for Analytics by IBMQuestDBSadas EngineXTDB infoformerly named Crux
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Netezza infoAlso called PureData System for Analytics by IBMQuestDBSadas EngineXTDB infoformerly named Crux
Recent citations in the 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

QuestDB snares $12M Series A with hosted version coming soon
3 November 2021, TechCrunch

SQL Extensions for Time-Series Data in QuestDB
11 January 2021, Towards Data Science

QuestDB gets $12M Series A funding amid growing interest in time-series databases
3 November 2021, SiliconANGLE News

Read the Pitch Deck Database Startup QuestDB Used to Raise $12 Million
11 November 2021, Business Insider

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

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