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DBMS > Apache Impala vs. Hawkular Metrics vs. HBase vs. KeyDB

System Properties Comparison Apache Impala vs. Hawkular Metrics vs. HBase vs. KeyDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Wide-column store based on Apache Hadoop and on concepts of BigTableAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMSTime Series DBMSWide column storeKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Websiteimpala.apache.orgwww.hawkular.orghbase.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationimpala.apache.org/­impala-docs.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmldocs.keydb.dev
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetEQ Alpha Technology Ltd.
Initial release2013201420082019
Current release4.1.0, June 20222.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache version 2Open Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaC++
Server operating systemsLinuxLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Linux
Data schemeyesschema-freeschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROpartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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.nononono
Secondary indexesyesnonoyes infoby using the Redis Search module
SQL infoSupport of SQLSQL-like DML and DDL statementsnonono
APIs and other access methodsJDBC
ODBC
HTTP RESTJava API
RESTful HTTP API
Thrift
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoCoprocessors in JavaLua
Triggersnoyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoSingle row ACID (across millions of columns)Optimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control and ACL

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More resources
Apache ImpalaHawkular MetricsHBaseKeyDB
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