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DBMS > Databricks vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Hawkular Metrics vs. OpenQM

System Properties Comparison Databricks vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Hawkular Metrics vs. OpenQM

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonOpenQM infoalso called QM  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.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.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.QpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database modelDocument store
Relational DBMS
Document storeDocument storeTime Series DBMSMultivalue DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Websitewww.databricks.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastorewww.hawkular.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentationdocs.databricks.comfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperDatabricksGoogle infoacquired by Google 2014GoogleCommunity supported by Red HatRocket Software, originally Martin Phillips
Initial release20132012200820141993
Current release3.4-12
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedhostedhostedLinux
OS X
Windows
AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-freeyes infowith some exceptions
Typing infopredefined data types such as float or dateyesyes, 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.yesnononoyes
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language (GQL)nono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
Supported programming languagesPython
R
Scala
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregateslimited functionality with using 'rules'using Google App Enginenoyes
TriggersCallbacks are triggered when data changesCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrayes
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate 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 integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
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.nonono
User concepts infoAccess controlyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights can be defined down to the item level
More information provided by the system vendor
DatabricksFirebase Realtime DatabaseGoogle Cloud DatastoreHawkular MetricsOpenQM infoalso called QM
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFirebase Realtime DatabaseGoogle Cloud DatastoreHawkular MetricsOpenQM infoalso called QM
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