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DBMS > Solr vs. Titan vs. Vertica

System Properties Comparison Solr vs. Titan vs. Vertica

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Editorial information provided by DB-Engines
NameSolr  Xexclude from comparisonTitan  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionA widely used distributed, scalable search engine based on Apache LuceneTitan is a Graph DBMS optimized for distributed clusters.Cloud 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 engineGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score41.02
Rank#24  Overall
#3  Search engines
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitesolr.apache.orggithub.com/­thinkaurelius/­titanwww.vertica.com
Technical documentationsolr.apache.org/­resources.htmlgithub.com/­thinkaurelius/­titan/­wikivertica.com/­documentation
DeveloperApache Software FoundationAurelius, owned by DataStaxOpenText infopreviously Micro Focus and Hewlett Packard
Initial release200620122005
Current release9.6.1, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache license, version 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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 languageJavaJavaC++
Server operating systemsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Unix
Windows
Linux
Data schemeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesYes, 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 dateyes infosupports customizable data types and automatic typingyesyes
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.yesno
Secondary indexesyes infoAll search fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSolr Parallel SQL InterfacenoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJava API
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Clojure
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava pluginsyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoUser configurable commands triggered on index changesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingyes infovia pluggable storage backendshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-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 methodsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infovia Faunus, a graph analytics engineno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyesUser authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
SolrTitanVertica 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...
» more
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
SolrTitanVertica infoOpenText™ Vertica™
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