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DBMS > Apache Impala vs. eXtremeDB vs. Riak KV vs. STSdb vs. Vertica

System Properties Comparison Apache Impala vs. eXtremeDB vs. Riak KV vs. STSdb vs. Vertica

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisoneXtremeDB  Xexclude from comparisonRiak KV  Xexclude from comparisonSTSdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopNatively in-memory DBMS with options for persistency, high-availability and clusteringDistributed, fault tolerant key-value storeKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexesKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.04
Rank#360  Overall
#52  Key-value stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteimpala.apache.orgwww.mcobject.comgithub.com/­STSSoft/­STSdb4www.vertica.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.mcobject.com/­docs/­extremedb.htmwww.tiot.jp/­riak-docs/­riak/­kv/­latestvertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMcObjectOpenSource, formerly Basho TechnologiesSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132001200920112005
Current release4.1.0, June 20228.2, 20213.2.0, December 20224.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPLv2, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++ErlangC#C++
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
WindowsLinux
Data schemeyesyesschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesnoyes infoprimitive types and user defined types (classes)yes
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.nono infosupport of XML interfaces availablenono
Secondary indexesyesyesrestrictednoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith the option: eXtremeSQLnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
HTTP API
Native Erlang Interface
.NET Client APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Java
Lua
Python
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesErlangnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infoby defining eventsyes infopre-commit hooks and post-commit hooksnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning / shardingSharding infono "single point of failure"nonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
selectable replication factornoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno infolinks between data sets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes, using Riak Securitynofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache ImpalaeXtremeDBRiak KVSTSdbVertica infoOpenText™ Vertica™
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
Apache ImpalaeXtremeDBRiak KVSTSdbVertica infoOpenText™ Vertica™
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