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DBMS > Apache IoTDB vs. Databricks vs. Google Cloud Datastore vs. InterSystems Caché

System Properties Comparison Apache IoTDB vs. Databricks vs. Google Cloud Datastore vs. InterSystems Caché

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkThe 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 PlatformA multi-model DBMS and application server
Primary database modelTime Series DBMSDocument store
Relational DBMS
Document storeKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websiteiotdb.apache.orgwww.databricks.comcloud.google.com/­datastorewww.intersystems.com/­products/­cache
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comcloud.google.com/­datastore/­docsdocs.intersystems.com
DeveloperApache Software FoundationDatabricksGoogleInterSystems
Initial release2018201320081997
Current release1.1.0, April 20232018.1.4, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemsAll OS with a Java VM (>= 1.8)hostedhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freedepending on used data model
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.noyesnoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLSQL-like query language (GQL)yes
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesusing Google App Engineyes
TriggersyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate 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 integritynoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnonoyes
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles
More information provided by the system vendor
Apache IoTDBDatabricksGoogle Cloud DatastoreInterSystems Caché
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache IoTDBDatabricksGoogle Cloud DatastoreInterSystems Caché
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