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DBMS > Databricks vs. Drizzle vs. HarperDB vs. JanusGraph vs. Kinetica

System Properties Comparison Databricks vs. Drizzle vs. HarperDB vs. JanusGraph vs. Kinetica

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonHarperDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonKinetica  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle 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.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.A Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Fully vectorized database across both GPUs and CPUs
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument storeGraph DBMSRelational DBMS
Secondary database modelsSpatial 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
Score0.55
Rank#248  Overall
#38  Document stores
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitewww.databricks.comwww.harperdb.iojanusgraph.orgwww.kinetica.com
Technical documentationdocs.databricks.comdocs.harperdb.io/­docsdocs.janusgraph.orgdocs.kinetica.com
DeveloperDatabricksDrizzle project, originally started by Brian AkerHarperDBLinux Foundation; originally developed as Titan by AureliusKinetica
Initial release20132008201720172012
Current release7.2.4, September 20123.1, August 20210.6.3, February 20237.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercial infofree community edition availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Node.jsJavaC, C++
Server operating systemshostedFreeBSD
Linux
OS X
Linux
OS X
Linux
OS X
Unix
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesdynamic schemayesyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes
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.yesnonono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsSQL-like data manipulation statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Clojure
Java
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoCustom Functions infosince release 3.1yesuser defined functions
Triggersno infohooks for callbacks inside the server can be used.noyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusteryes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
yes infothe nodes on which a table resides can be definedyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic execution of specific operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and rolesUser authentification and security via Rexster Graph ServerAccess rights for users and roles on table level
More information provided by the system vendor
DatabricksDrizzleHarperDBJanusGraph infosuccessor of TitanKinetica
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDrizzleHarperDBJanusGraph infosuccessor of TitanKinetica
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