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DBMS > Apache Spark (SQL) vs. Titan

System Properties Comparison Apache Spark (SQL) vs. Titan

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Our visitors often compare Apache Spark (SQL) and Titan with PostgreSQL, Neo4j and Apache Ignite.

Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonTitan  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.
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score21.62
Rank#29  Overall
#18  Relational DBMS
Websitespark.apache.org/­sqlgithub.com/­thinkaurelius/­titan
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software FoundationAurelius, owned by DataStax
Initial release20142012
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJava
Server operating systemsLinux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.no
Secondary indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesJava
Python
R
Scala
Clojure
Java
Python
Server-side scripts infoStored proceduresnoyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Coreyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlnoUser authentification and security via Rexster Graph Server

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More resources
Apache Spark (SQL)Titan
DB-Engines blog posts

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