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DBMS > Databricks vs. GridDB vs. Memgraph vs. Sphinx

System Properties Comparison Databricks vs. GridDB vs. Memgraph vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridDB  Xexclude from comparisonMemgraph  Xexclude from comparisonSphinx  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.Scalable in-memory time series database optimized for IoT and Big DataAn open source graph database built for real-time streaming and compatible with Neo4jOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Time Series DBMSGraph DBMSSearch engine
Secondary database modelsKey-value store
Relational 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score3.02
Rank#98  Overall
#8  Graph DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comgriddb.netmemgraph.comsphinxsearch.com
Technical documentationdocs.databricks.comdocs.griddb.netmemgraph.com/­docssphinxsearch.com/­docs
Social network pagesLinkedInTwitterFacebookGitHubDiscord
DeveloperDatabricksToshiba CorporationMemgraph LtdSphinx Technologies Inc.
Initial release2013201320172001
Current release5.1, August 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoBSL 1.1; commercial license for enterprise edition availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C++
Server operating systemshostedLinuxLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free and schema-optionalyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesno
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 infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Bolt protocol
Cypher query language
Proprietary protocol
Supported programming languagesPython
R
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infodynamic graph partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication using RAFTnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID infowith snapshot isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infowith periodic snapshot and write-ahead logging (WAL) of changesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseUsers, roles and permissionsno
More information provided by the system vendor
DatabricksGridDBMemgraphSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Memgraph directly connects to your streaming infrastructure so you and your team...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Business Source License ensures a future for the Memgraph community MAGE algorithm...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
You can check out our pricing model and licenses on the company website .
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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DatabricksGridDBMemgraphSphinx
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