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DBMS > Google Cloud Bigtable vs. Graph Engine vs. MarkLogic vs. Microsoft Azure Synapse Analytics vs. Pinecone

System Properties Comparison Google Cloud Bigtable vs. Graph Engine vs. MarkLogic vs. Microsoft Azure Synapse Analytics vs. Pinecone

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineOperational and transactional Enterprise NoSQL databaseElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA managed, cloud-native vector database
Primary database modelKey-value store
Wide column store
Graph DBMS
Key-value store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Websitecloud.google.com/­bigtablewww.graphengine.iowww.marklogic.comazure.microsoft.com/­services/­synapse-analyticswww.pinecone.io
Technical documentationcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualdocs.marklogic.comdocs.microsoft.com/­azure/­synapse-analyticsdocs.pinecone.io/­docs/­overview
DeveloperGoogleMicrosoftMarkLogic Corp.MicrosoftPinecone Systems, Inc
Initial release20152010200120162019
Current release11.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoMIT Licensecommercial inforestricted free version is availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CC++C++
Server operating systemshosted.NETLinux
OS X
Windows
hostedhosted
Data schemeschema-freeyesschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or datenoyesyesyesString, Number, Boolean
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.nonoyesnono
Secondary indexesnoyesyes
SQL infoSupport of SQLnonoyes infoSQL92yesno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
PHP
Python
Server-side scripts infoStored proceduresnoyesyes infovia XQuery or JavaScriptTransact SQL
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levelsyes

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More resources
Google Cloud BigtableGraph Engine infoformer name: TrinityMarkLogicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehousePinecone
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