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DBMS > EventStoreDB vs. Google Cloud Bigtable vs. Google Cloud Firestore vs. MarkLogic vs. Spark SQL

System Properties Comparison EventStoreDB vs. Google Cloud Bigtable vs. Google Cloud Firestore vs. MarkLogic vs. Spark SQL

Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Operational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelEvent StoreKey-value store
Wide column store
Document storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.10
Rank#179  Overall
#1  Event Stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score7.85
Rank#51  Overall
#8  Document stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.eventstore.comcloud.google.com/­bigtablefirebase.google.com/­products/­firestorewww.marklogic.comspark.apache.org/­sql
Technical documentationdevelopers.eventstore.comcloud.google.com/­bigtable/­docsfirebase.google.com/­docs/­firestoredocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEvent Store LimitedGoogleGoogleMarkLogic Corp.Apache Software Foundation
Initial release20122015201720012014
Current release21.2, February 202111.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsLinux
Windows
hostedhostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonoyesno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnonoyes infoSQL92SQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP 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
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes infovia XQuery or JavaScriptno
Triggersnoyes, with Cloud Functionsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud Dataflowyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
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
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsyesACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyes, with Range Indexesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Role-based access control at the document and subdocument levelsno

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More resources
EventStoreDBGoogle Cloud BigtableGoogle Cloud FirestoreMarkLogicSpark SQL
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