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DBMS > Google Cloud Spanner vs. Neo4j vs. Splice Machine vs. SurrealDB

System Properties Comparison Google Cloud Spanner vs. Neo4j vs. Splice Machine vs. SurrealDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonNeo4j  Xexclude from comparisonSplice Machine  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionA 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 offeringsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelRelational DBMSGraph DBMSRelational DBMSDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.56
Rank#97  Overall
#50  Relational DBMS
Score47.91
Rank#20  Overall
#1  Graph DBMS
Score0.54
Rank#243  Overall
#114  Relational DBMS
Score1.08
Rank#176  Overall
#30  Document stores
#16  Graph DBMS
Websitecloud.google.com/­spannerneo4j.comsplicemachine.comsurrealdb.com
Technical documentationcloud.google.com/­spanner/­docsneo4j.com/­docssplicemachine.com/­how-it-workssurrealdb.com/­docs
DeveloperGoogleNeo4j, Inc.Splice MachineSurrealDB Ltd
Initial release2017200720142022
Current release5.23, August 20243.1, March 2021v1.5.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoAGPL 3.0, commercial license availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ScalaJavaRust
Server operating systemshostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyesschema-free and schema-optionalyesschema-free
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.no
Secondary indexesyesyes infopluggable indexing subsystem, by default Apache Luceneyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011noyesSQL-like query language
APIs and other access methodsgRPC (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
Native Spark Datasource
ODBC
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresnoyes infoUser defined Procedures and Functionsyes infoJava
Triggersnoyes infovia event handleryes
Partitioning methods infoMethods for storing different data on different nodesShardingyes using Neo4j FabricShared Nothhing Auto-Sharding, Columnar Partitioning
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 onlyMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.noyes
User concepts infoAccess controlAccess 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)Access rights for users, groups and roles according to SQL-standardyes, based on authentication and database rules
More information provided by the system vendor
Google Cloud SpannerNeo4jSplice MachineSurrealDB
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22 March 2025, infoq.com

New features make Google's Spanner a database for AI
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23 July 2024, InfoWorld

Google Cloud adds graph and vector search features to Spanner database
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Google Releases Spanner Graph into General Availability
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Neo4j Launches Industry's First Graph Analytics Offering For Any Data Platform
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