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DBMS > Amazon DocumentDB vs. Lovefield vs. Vertica vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Lovefield vs. Vertica vs. Yaacomo

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonLovefield  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceEmbeddable relational database for web apps written in pure JavaScriptCloud 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeRelational DBMSRelational DBMS infoColumn orientedRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.80
Rank#148  Overall
#25  Document stores
Score0.35
Rank#286  Overall
#131  Relational DBMS
Score11.76
Rank#44  Overall
#28  Relational DBMS
Websiteaws.amazon.com/­documentdbgoogle.github.io/­lovefieldwww.vertica.comyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcesgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdvertica.com/­documentation
DeveloperGoogleOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release2019201420052009
Current release2.1.12, February 201712.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud serviceyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptC++
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinuxAndroid
Linux
Windows
Data schemeschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
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.nononono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLnoSQL-like query language infovia JavaScript builder patternFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
JavaScriptC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersnoUsing read-only observersyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDBnoyes
User concepts infoAccess controlAccess rights for users and rolesnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon DocumentDBLovefieldVertica infoOpenText™ Vertica™Yaacomo
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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Amazon DocumentDBLovefieldVertica infoOpenText™ Vertica™Yaacomo
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