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DBMS > Databricks vs. Ehcache vs. HEAVY.AI vs. IRONdb vs. Kinetica

System Properties Comparison Databricks vs. Ehcache vs. HEAVY.AI vs. IRONdb vs. Kinetica

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded 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.A widely adopted Java cache with tiered storage optionsA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUs
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series 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
Score4.89
Rank#67  Overall
#8  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitewww.databricks.comwww.ehcache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.circonus.com/solutions/time-series-database/www.kinetica.com
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationdocs.heavy.aidocs.circonus.com/irondb/category/getting-starteddocs.kinetica.com
DeveloperDatabricksTerracotta Inc, owned by Software AGHEAVY.AI, Inc.Circonus LLC.Kinetica
Initial release20132009201620172012
Current release3.10.0, March 20225.10, January 2022V0.10.20, January 20187.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ and CUDAC and C++C, C++
Server operating systemshostedAll OS with a Java VMLinuxLinuxLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyes
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.yesnononono
Secondary indexesyesnononoyes
SQL infoSupport of SQLwith Databricks SQLnoyesSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheJDBC
ODBC
Thrift
Vega
HTTP APIJDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
JavaAll languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes, in Luauser defined functions
Triggersyes infoCache Event Listenersnonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding infoRound robinAutomatic, metric affinity per nodeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta ServerMulti-source replicationconfigurable replication factor, datacenter awareSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourcenonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlnofine grained access rights according to SQL-standardnoAccess rights for users and roles on table level
More information provided by the system vendor
DatabricksEhcacheHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IRONdbKinetica
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEhcacheHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IRONdbKinetica
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