DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > AnzoGraph DB vs. Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. Vitess

System Properties Comparison AnzoGraph DB vs. Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Database as a Service offering with high compatibility to Microsoft SQL ServerScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelGraph DBMS
RDF store
Key-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitecambridgesemantics.com/­anzographcloud.google.com/­bigtableazure.microsoft.com/­en-us/­products/­azure-sql/­databasevitess.io
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlvitess.io/­docs
DeveloperCambridge SemanticsGoogleMicrosoftThe Linux Foundation, PlanetScale
Initial release2018201520102013
Current release2.3, January 2021V1215.0.2, December 2022
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Go
Server operating systemsLinuxhostedhostedDocker
Linux
macOS
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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.nonoyes
Secondary indexesnonoyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.noyesyes infowith proprietary extensions
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoTransact SQLyes infoproprietary syntax
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterInternal replication in Colossus, and regional replication between two clusters in different zonesyes, with always 3 replicas availableMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityno infonot needed in graphsnoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
AnzoGraph DBGoogle Cloud BigtableMicrosoft Azure SQL Database infoformerly SQL AzureVitess
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

show all

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Unveils AnzoGraph DB with Geospatial Analytics
19 June 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

provided by Google News

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

Copilot in Azure SQL Database in Private Preview
27 March 2024, InfoQ.com

Microsoft unveils Copilot for Azure SQL Database
27 March 2024, InfoWorld

Azure SQL Database migration to OCI - resources estimation and migration approach
11 January 2024, blogs.oracle.com

Expand the limits of innovation with Azure data
21 March 2024, microsoft.com

Why migrate Windows Server and SQL Server to Azure: ROI, innovation, and free offers
25 April 2024, microsoft.com

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here