DBMS > Google Cloud Spanner vs. GraphDB vs. RocksDB vs. SurrealDB

System Properties Comparison Google Cloud Spanner vs. GraphDB vs. RocksDB vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Description

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.

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS

Graph DBMS
RDF store

Key-value store

Document store
Graph DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Website

cloud.google.com/spanner

www.ontotext.com

rocksdb.org

surrealdb.com

Technical documentation

cloud.google.com/spanner/docs

graphdb.ontotext.com/documentation

github.com/facebook/rocksdb/wiki

surrealdb.com/docs

Social network pages

Developer

Google

Ontotext

Facebook, Inc.

SurrealDB Ltd

Initial release

2017

2000

2013

2022

Current release

10.4, October 2023

8.11.4, April 2024

v1.1.1, January 2024

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

BSD

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Rust

Server operating systems

hosted

All OS with a Java VM
Linux
OS X
Windows

Linux

Linux
macOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support; RDF shapes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

SQL-like query language

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

C++ API
Java API

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Constraint checking

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Strict serializable isolation

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

yes, based on authentication and database rules

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Understanding the Graph Center of Excellence
17 May 2024

Migrating From LPG to RDF Graph Model
8 May 2024

Case study: Policy Enforcement Automation With Semantics
2 May 2024

Okay, RAG… We Have a Problem
26 April 2024

Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP
19 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.