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DBMS > Databricks vs. DolphinDB vs. Heroic vs. Sphinx vs. Splice Machine

System Properties Comparison Databricks vs. DolphinDB vs. Heroic vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDolphinDB  Xexclude from comparisonHeroic  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  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.DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Relational DBMS
Time Series DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsRelational 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
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.databricks.comwww.dolphindb.comgithub.com/­spotify/­heroicsphinxsearch.comsplicemachine.com
Technical documentationdocs.databricks.comdocs.dolphindb.cn/­en/­help200/­index.htmlspotify.github.io/­heroicsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperDatabricksDolphinDB, IncSpotifySphinx Technologies Inc.Splice Machine
Initial release20132018201420012014
Current releasev2.00.4, January 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infofree community version availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++Java
Server operating systemshostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.yesnono
Secondary indexesyesyesyes infovia Elasticsearchyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query languagenoSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnonoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAdministrators, Users, GroupsnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksDolphinDBHeroicSphinxSplice Machine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDolphinDBHeroicSphinxSplice Machine
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