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DBMS > Amazon CloudSearch vs. Apache Impala vs. Datomic vs. Vertica

System Properties Comparison Amazon CloudSearch vs. Apache Impala vs. Datomic vs. Vertica

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud 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 modelSearch engineRelational DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.87
Rank#140  Overall
#12  Search engines
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websiteaws.amazon.com/­cloudsearchimpala.apache.orgwww.datomic.comwww.vertica.com
Technical documentationdocs.aws.amazon.com/­cloudsearchimpala.apache.org/­impala-docs.htmldocs.datomic.comvertica.com/­documentation
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012201320122005
Current release4.1.0, June 20221.0.6735, June 202312.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infolimited edition freecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnonono 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++Java, ClojureC++
Server operating systemshostedLinuxAll OS with a Java VMLinux
Data schemeyesyesyesYes, 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 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 indexesyes infoall search fields are automatically indexedyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP APIJDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyes, PostgreSQL PL/pgSQL, with minor differences
TriggersnonoBy using transaction functionsyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingnone infoBut extensive use of caching in the application peershorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSselectable replication factornone infoBut extensive use of caching in the application peersMulti-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 methodsnoyes infoquery execution via MapReducenono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
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 developmentno
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Amazon CloudSearchApache ImpalaDatomicVertica 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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More resources
Amazon CloudSearchApache ImpalaDatomicVertica infoOpenText™ Vertica™
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