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DBMS > Apache Impala vs. CouchDB vs. InfinityDB vs. mSQL vs. Vertica

System Properties Comparison Apache Impala vs. CouchDB vs. InfinityDB vs. mSQL vs. Vertica

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonInfinityDB  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.A Java embedded Key-Value Store which extends the Java Map interfacemSQL (Mini SQL) is a simple and lightweight RDBMSCloud 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 DBMSDocument storeKey-value storeRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial DBMS infousing the Geocouch extensionSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score8.30
Rank#47  Overall
#7  Document stores
Score0.08
Rank#365  Overall
#55  Key-value stores
Score1.27
Rank#169  Overall
#76  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteimpala.apache.orgcouchdb.apache.orgboilerbay.comhughestech.com.au/­products/­msqlwww.vertica.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.couchdb.org/­en/­stableboilerbay.com/­infinitydb/­manualvertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerBoiler Bay Inc.Hughes TechnologiesOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132005200219942005
Current release4.1.0, June 20223.3.3, December 20234.04.4, October 202112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache version 2commercialcommercial infofree licenses can be providedcommercial 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

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Implementation languageC++ErlangJavaCC++
Server operating systemsLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Data schemeyesschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesYes, 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 dateyesnoyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.nonononono
Secondary indexesyesyes infovia viewsno infomanual creation possible, using inversions based on multi-value capabilityyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP/JSON APIAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
JavaC
C++
Delphi
Java
Perl
PHP
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceView functions in JavaScriptnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0nonenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
nonenoneMulti-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 MapReduceyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDnoneImmediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilitynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single document possibleACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesnoyes
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.nonononono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databasenonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache ImpalaCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"InfinityDBmSQL infoMini SQLVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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Apache ImpalaCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"InfinityDBmSQL infoMini SQLVertica infoOpenText™ Vertica™
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