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DBMS > Databricks vs. EXASOL vs. Google Cloud Datastore vs. Manticore Search

System Properties Comparison Databricks vs. EXASOL vs. Google Cloud Datastore vs. Manticore Search

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparison
DescriptionThe 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.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument storeSearch engine
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score0.23
Rank#317  Overall
#21  Search engines
Websitewww.databricks.comwww.exasol.comcloud.google.com/­datastoremanticoresearch.com
Technical documentationdocs.databricks.comwww.exasol.com/­resourcescloud.google.com/­datastore/­docsmanual.manticoresearch.com
DeveloperDatabricksExasolGoogleManticore Software
Initial release2013200020082017
Current release6.0, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedhostedFreeBSD
Linux
macOS
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeFixed schema
Typing infopredefined data types such as float or dateyesyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.yesnonoCan index from XML
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query language (GQL)SQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesPython
R
Scala
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsusing Google App Engineuser defined functions
TriggersyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyes 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.
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 Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
DatabricksEXASOLGoogle Cloud DatastoreManticore Search
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEXASOLGoogle Cloud DatastoreManticore Search
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