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DBMS > Databricks vs. eXtremeDB vs. InfinityDB vs. Riak KV

System Properties Comparison Databricks vs. eXtremeDB vs. InfinityDB vs. Riak KV

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisoneXtremeDB  Xexclude from comparisonInfinityDB  Xexclude from comparisonRiak KV  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.Natively in-memory DBMS with options for persistency, high-availability and clusteringA Java embedded Key-Value Store which extends the Java Map interfaceDistributed, fault tolerant key-value store
Primary database modelDocument store
Relational DBMS
Relational DBMS
Time Series DBMS
Key-value storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitewww.databricks.comwww.mcobject.comboilerbay.com
Technical documentationdocs.databricks.comwww.mcobject.com/­docs/­extremedb.htmboilerbay.com/­infinitydb/­manualwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperDatabricksMcObjectBoiler Bay Inc.OpenSource, formerly Basho Technologies
Initial release2013200120022009
Current release8.2, 20214.03.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaErlang
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
All OS with a Java VMLinux
OS X
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-free
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysno
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.yesno infosupport of XML interfaces availablenono
Secondary indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityrestricted
SQL infoSupport of SQLwith Databricks SQLyes infowith the option: eXtremeSQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP API
Native Erlang Interface
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
JavaC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnoErlang
Triggersyes infoby defining eventsnoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingnoneSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
noneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual Consistency
Foreign keys infoReferential integrityyesno infomanual creation possible, using inversions based on multi-value capabilityno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.noyesno
User concepts infoAccess controlnoyes, using Riak Security
More information provided by the system vendor
DatabrickseXtremeDBInfinityDBRiak KV
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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DatabrickseXtremeDBInfinityDBRiak KV
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