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DBMS > Apache Impala vs. Databend vs. Informix vs. Quasardb

System Properties Comparison Apache Impala vs. Databend vs. Informix vs. Quasardb

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabend  Xexclude from comparisonInformix  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataDistributed, high-performance timeseries database
Primary database modelRelational DBMSRelational DBMSRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBTime Series DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websiteimpala.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
www.ibm.com/­products/­informixquasar.ai
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databend.cominformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
doc.quasar.ai/­master
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabend LabsIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.quasardb
Initial release2013202119842009
Current release4.1.0, June 20221.0.59, April 202314.10.FC5, November 20203.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial infofree developer edition availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
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++RustC, C++ and JavaC++
Server operating systemsLinuxhosted
Linux
macOS
AIX
HP-UX
Linux
macOS
Solaris
Windows
BSD
Linux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infoSince Version 12.10 support for JSON/BSON datatypesyes infointeger and binary
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 infowith tags
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesSQL-like query language
APIs and other access methodsJDBC
ODBC
CLI Client
JDBC
RESTful HTTP API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication
Source-replica replication
Source-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoTransient mode
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization concept, user rolesUsers with fine-grained authentication, authorization, and auditing controlsCryptographically strong user authentication and audit trail

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More resources
Apache ImpalaDatabendInformixQuasardb
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