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DBMS > Apache Impala vs. Datomic vs. Netezza vs. QuestDB

System Properties Comparison Apache Impala vs. Datomic vs. Netezza vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityData warehouse and analytics appliance part of IBM PureSystemsA high performance open source SQL database for time series data
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websiteimpala.apache.orgwww.datomic.comwww.ibm.com/­products/­netezzaquestdb.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comquestdb.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectIBMQuestDB Technology Inc
Initial release2013201220002014
Current release4.1.0, June 20221.0.6735, June 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureJava (Zero-GC), C++, Rust
Server operating systemsLinuxAll OS with a Java VMLinux infoincluded in applianceLinux
macOS
Windows
Data schemeyesyesyesyes infoschema-free via InfluxDB Line Protocol
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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesSQL with time-series extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJDBC
ODBC
OLE DB
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
C
C++
Fortran
Java
Lua
Perl
Python
R
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyesno
TriggersnoBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersSource-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoUsers with fine-grained authorization concept
More information provided by the system vendor
Apache ImpalaDatomicNetezza infoAlso called PureData System for Analytics by IBMQuestDB
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
Apache ImpalaDatomicNetezza infoAlso called PureData System for Analytics by IBMQuestDB
Recent citations in the news

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29 July 2021, iProgrammer

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Q&A: Nicolas Hourcard, QuestDB: The advantages of a time-series database
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