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DBMS > EXASOL vs. Google Cloud Spanner vs. Neo4j vs. Spark SQL

System Properties Comparison EXASOL vs. Google Cloud Spanner vs. Neo4j vs. Spark SQL

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonNeo4j  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.exasol.comcloud.google.com/­spannerneo4j.comspark.apache.org/­sql
Technical documentationwww.exasol.com/­resourcescloud.google.com/­spanner/­docsneo4j.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolGoogleNeo4j, Inc.Apache Software Foundation
Initial release2000201720072014
Current release5.20, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJava, ScalaScala
Server operating systemshostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesschema-free and schema-optionalyes
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.nonono
Secondary indexesyesyesyes infopluggable indexing subsystem, by default Apache Luceneno
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011noSQL-like DML and DDL statements
APIs and other access methods.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
JDBC
ODBC
Supported programming languagesJava
Lua
Python
R
Go
Java
JavaScript (Node.js)
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoyes infoUser defined Procedures and Functionsno
Triggersyesnoyes infovia event handlerno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes using Neo4j Fabricyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.Causal Clustering using Raft protocol infoavailable in in Enterprise Version onlynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)no
More information provided by the system vendor
EXASOLGoogle Cloud SpannerNeo4jSpark SQL
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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