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DBMS > atoti vs. Dolt vs. Google Cloud Datastore vs. Sequoiadb vs. Spark SQL

System Properties Comparison atoti vs. Dolt vs. Google Cloud Datastore vs. Sequoiadb vs. Spark SQL

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonDolt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A MySQL compatible DBMS with Git-like versioning of data and schemaAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSRelational DBMSDocument storeDocument store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score1.02
Rank#191  Overall
#89  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iogithub.com/­dolthub/­dolt
www.dolthub.com
cloud.google.com/­datastorewww.sequoiadb.comspark.apache.org/­sql
Technical documentationdocs.atoti.iodocs.dolthub.comcloud.google.com/­datastore/­docswww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamDoltHub IncGoogleSequoiadb Ltd.Apache Software Foundation
Initial release2018200820132014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache Version 2.0commercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++Scala
Server operating systemsLinux
macOS
Windows
hostedLinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyes infooid, date, timestamp, binary, regexyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)yesSQL-like query language (GQL)SQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsCLI Client
HTTP REST
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonyes infocurrently in alpha releaseusing Google App EngineJavaScriptno
TriggersyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.Multi-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
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.yesnonono
User concepts infoAccess controlOnly one user is configurable, and must be specified in the config file at startupAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access controlno

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More resources
atotiDoltGoogle Cloud DatastoreSequoiadbSpark SQL
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