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DBMS > AgensGraph vs. Hive vs. Oracle Rdb vs. Solr vs. Vertica

System Properties Comparison AgensGraph vs. Hive vs. Oracle Rdb vs. Solr vs. Vertica

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonHive  Xexclude from comparisonOracle Rdb  Xexclude from comparisonSolr  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLdata warehouse software for querying and managing large distributed datasets, built on HadoopA widely used distributed, scalable search engine based on Apache LuceneCloud 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 modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score1.14
Rank#178  Overall
#80  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitebitnine.net/­agensgraphhive.apache.orgwww.oracle.com/­database/­technologies/­related/­rdb.htmlsolr.apache.orgwww.vertica.com
Technical documentationbitnine.net/­documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlsolr.apache.org/­resources.htmlvertica.com/­documentation
DeveloperBitnine Global Inc.Apache Software Foundation infoinitially developed by FacebookOracle, originally developed by Digital Equipment Corporation (DEC)Apache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20162012198420062005
Current release2.1, December 20183.1.3, April 20227.4.1.1, 20219.6.1, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2commercialOpen Source infoApache Version 2commercial 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 languageCJavaJavaC++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMHP Open VMSAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemedepending on used data modelyesFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fieldsYes, 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 infosupports customizable data types and automatic typingyes
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.nonoyesno
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyesSolr Parallel SQL InterfaceFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsCypher Query Language
JDBC
JDBC
ODBC
Thrift
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
Java
JavaScript
Python
C++
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceJava pluginsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes infoUser configurable commands triggered on index changesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryesMulti-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 MapReducenospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes, on a single nodeoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
AgensGraphHiveOracle RdbSolrVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
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
AgensGraphHiveOracle RdbSolrVertica infoOpenText™ Vertica™
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