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

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

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonjBASE  Xexclude from comparisonMarkLogic  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  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 robust multi-value DBMS comprising development tools and middlewareOperational 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 Server
Primary database modelKey-value store
Wide column store
Multivalue DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Key-value storeRelational 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
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
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
Websitecloud.google.com/­bigtablewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.marklogic.comwww.memcached.orgazure.microsoft.com/­services/­synapse-analytics
Technical documentationcloud.google.com/­bigtable/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.marklogic.comgithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­azure/­synapse-analytics
DeveloperGoogleRocket Software (formerly Zumasys)MarkLogic Corp.Danga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoft
Initial release20151991200120032016
Current release5.711.0, December 20221.6.27, May 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source infoBSD licensecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC++
Server operating systemshostedAIX
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
OS X
Unix
Windows
hosted
Data schemeschema-freeschema-freeschema-free infoSchema can be enforcedschema-freeyes
Typing infopredefined data types such as float or datenooptionalyesnoyes
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.noyesyesno
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoEmbedded SQL for jBASE in BASICyes infoSQL92noyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
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
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Basic
Jabbascript
Java
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
Server-side scripts infoStored proceduresnoyesyes infovia XQuery or JavaScriptnoTransact SQL
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesyesnone infoRepcached, a Memcached patch, provides this functionallityyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes 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 integritynonononono 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 operationsACIDACID infocan act as a resource manager in an XA/JTA transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item levelRole-based access control at the document and subdocument levelsyes infousing SASL (Simple Authentication and Security Layer) protocolyes

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More resources
Google Cloud BigtablejBASEMarkLogicMemcachedMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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