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DBMS > Apache Spark (SQL) vs. Datastax Enterprise vs. Neo4j

System Properties Comparison Apache Spark (SQL) vs. Datastax Enterprise vs. Neo4j

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonNeo4j  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings
Primary database modelRelational DBMSWide column storeGraph DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.45
Rank#31  Overall
#19  Relational DBMS
Score4.22
Rank#65  Overall
#4  Wide column stores
Score45.34
Rank#20  Overall
#1  Graph DBMS
Websitespark.apache.org/­sqlwww.datastax.com/­products/­datastax-enterpriseneo4j.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.datastax.comneo4j.com/­docs
DeveloperApache Software FoundationDataStaxNeo4j, Inc.
Initial release201420112007
Current release3.5.0 ( 2.13), September 20236.8, April 20205.23, August 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPL version3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaJava, Scala
Server operating systemsLinux
OS X
Windows
Linux
OS X
Linux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Data schemeyesschema-freeschema-free and schema-optional
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesnoyesyes infopluggable indexing subsystem, by default Apache Lucene
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL); Spark SQLno
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoyes infoUser defined Procedures and Functions
Triggersnoyesyes infovia event handler
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infono "single point of failure"yes using Neo4j Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesnoneconfigurable replication factor, datacenter aware, advanced replication for edge computingCausal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integritynonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnoAccess rights for users can be defined per objectUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
Apache Spark (SQL)Datastax EnterpriseNeo4j
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Neo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Neo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsAnnual subscription
» more
GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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