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DBMS > Google Cloud Bigtable vs. MarkLogic vs. Memcached vs. Microsoft Azure Synapse Analytics vs. YDB

System Properties Comparison Google Cloud Bigtable vs. MarkLogic vs. Memcached vs. Microsoft Azure Synapse Analytics vs. YDB

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonYDB  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.Operational and transactional Enterprise NoSQL databaseIn-memory key-value store, originally intended for cachingElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Key-value storeRelational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score18.08
Rank#32  Overall
#4  Key-value stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitecloud.google.com/­bigtablewww.marklogic.comwww.memcached.orgazure.microsoft.com/­services/­synapse-analyticsgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationcloud.google.com/­bigtable/­docsdocs.marklogic.comgithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­azure/­synapse-analyticsydb.tech/­en/­docs
DeveloperGoogleMarkLogic Corp.Danga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftYandex
Initial release20152001200320162019
Current release11.0, December 20221.6.27, May 2024
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoBSD licensecommercialOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC++
Server operating systemshostedLinux
OS X
Windows
FreeBSD
Linux
OS X
Unix
Windows
hostedLinux
Data schemeschema-freeschema-free infoSchema can be enforcedschema-freeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or datenoyesnoyesyes
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.noyesnono
Secondary indexesnoyesnoyesyes
SQL infoSupport of SQLnoyes infoSQL92noyesSQL-like query language (YQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Proprietary protocolADO.NET
JDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
Java
PHP
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptnoTransact SQLno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesnone infoRepcached, a Memcached patch, provides this functionallityyesActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnonono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transactionnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, 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 infousing SASL (Simple Authentication and Security Layer) protocolyesAccess rights defined for Yandex Cloud users

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More resources
Google Cloud BigtableMarkLogicMemcachedMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseYDB
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