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DBMS > Amazon Redshift vs. Databricks vs. HEAVY.AI vs. RRDtool vs. Yaacomo

System Properties Comparison Amazon Redshift vs. Databricks vs. HEAVY.AI vs. RRDtool vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonDatabricks  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonRRDtool  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionLarge scale data warehouse service for use with business intelligence toolsThe 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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Websiteaws.amazon.com/­redshiftwww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
oss.oetiker.ch/­rrdtoolyaacomo.com
Technical documentationdocs.aws.amazon.com/­redshiftdocs.databricks.comdocs.heavy.aioss.oetiker.ch/­rrdtool/­doc
DeveloperAmazon (based on PostgreSQL)DatabricksHEAVY.AI, Inc.Tobias OetikerQ2WEB GmbH
Initial release20122013201619992009
Current release5.10, January 20221.8.0, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGPL V2 and FLOSScommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++ and CUDAC infoImplementations in Java (e.g. RRD4J) and C# available
Server operating systemshostedhostedLinuxHP-UX
Linux
Android
Linux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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.noyesnono infoExporting into and restoring from XML files possibleno
Secondary indexesrestrictedyesnonoyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardwith Databricks SQLyesnoyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
in-process shared library
Pipes
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functions and aggregatesnono
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoby using the rrdcached daemonyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon RedshiftDatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022RRDtoolYaacomo
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon RedshiftDatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022RRDtoolYaacomo
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