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DBMS > Databricks vs. Google Cloud Datastore vs. Hawkular Metrics vs. InterSystems Caché vs. STSdb

System Properties Comparison Databricks vs. Google Cloud Datastore vs. Hawkular Metrics vs. InterSystems Caché vs. STSdb

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSTSdb  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A multi-model DBMS and application serverKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument store
Relational DBMS
Document storeTime Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Key-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.databricks.comcloud.google.com/­datastorewww.hawkular.orgwww.intersystems.com/­products/­cachegithub.com/­STSSoft/­STSdb4
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.intersystems.com
DeveloperDatabricksGoogleCommunity supported by Red HatInterSystemsSTS Soft SC
Initial release20132008201419972011
Current release2018.1.4, May 20204.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#
Server operating systemshostedhostedLinux
OS X
Windows
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freedepending on used data modelyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes infoprimitive types and user defined types (classes)
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 indexesyesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (GQL)noyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST.NET Client API
JDBC
ODBC
RESTful HTTP API
.NET Client API
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C#
C++
Java
C#
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Enginenoyesno
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandranonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosselectable replication factor infobased on CassandraSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and rolesno
More information provided by the system vendor
DatabricksGoogle Cloud DatastoreHawkular MetricsInterSystems CachéSTSdb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGoogle Cloud DatastoreHawkular MetricsInterSystems CachéSTSdb
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