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DBMS > atoti vs. Databricks vs. Fauna vs. Google Cloud Datastore vs. searchxml

System Properties Comparison atoti vs. Databricks vs. Fauna vs. Google Cloud Datastore vs. searchxml

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonDatabricks  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonsearchxml  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for structured and unstructured content wrapped with an application server
Primary database modelObject oriented DBMSDocument store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Document storeNative XML DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Websiteatoti.iowww.databricks.comfauna.comcloud.google.com/­datastorewww.searchxml.net/­category/­products
Technical documentationdocs.atoti.iodocs.databricks.comdocs.fauna.comcloud.google.com/­datastore/­docswww.searchxml.net/­support/­handouts
DeveloperActiveViamDatabricksFauna, Inc.Googleinformationpartners gmbh
Initial release2013201420082015
Current release1.0
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaC++
Server operating systemshostedhostedhostedWindows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenoyes, details hereyes
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.yesnonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)with Databricks SQLnoSQL-like query language (GQL)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languagesPython
R
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresPythonuser defined functions and aggregatesuser defined functionsusing Google App Engineyes infoon the application server
TriggersnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioninghorizontal partitioning infoconsistent hashingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationMulti-source replication using Paxosyes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate 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.Immediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsmultiple readers, single writer
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.yesnononono
User concepts infoAccess controlIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Domain, group and role-based access control at the document level and for application services
More information provided by the system vendor
atotiDatabricksFauna infopreviously named FaunaDBGoogle Cloud Datastoresearchxml
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
atotiDatabricksFauna infopreviously named FaunaDBGoogle Cloud Datastoresearchxml
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