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DBMS > Drizzle vs. Google Cloud Bigtable vs. MarkLogic vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. MarkLogic vs. Microsoft Azure Synapse Analytics vs. Spark SQL

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Google'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 databaseElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational 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
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­bigtablewww.marklogic.comazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationcloud.google.com/­bigtable/­docsdocs.marklogic.comdocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDrizzle project, originally started by Brian AkerGoogleMarkLogic Corp.MicrosoftApache Software Foundation
Initial release20082015200120162014
Current release7.2.4, September 201211.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercial inforestricted free version is availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++Scala
Server operating systemsFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeyesschema-freeschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 indexesyesnoyesyesno
SQL infoSupport of SQLyes infowith proprietary extensionsnoyes infoSQL92yesSQL-like DML and DDL statements
APIs and other access methodsJDBCgRPC (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
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infovia XQuery or JavaScriptTransact SQLno
Triggersno infohooks for callbacks inside the server can be used.noyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
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 integrityyesnonono 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 dataACIDAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transactionACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levelsyesno

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More resources
DrizzleGoogle Cloud BigtableMarkLogicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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