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DBMS > Databricks vs. Heroic vs. SingleStore

System Properties Comparison Databricks vs. Heroic vs. SingleStore

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHeroic  Xexclude from comparisonSingleStore infoformer name was MemSQL  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.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score85.60
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.02
Rank#365  Overall
#37  Time Series DBMS
Score4.11
Rank#70  Overall
#38  Relational DBMS
Websitewww.databricks.comgithub.com/­spotify/­heroicwww.singlestore.com
Technical documentationdocs.databricks.comspotify.github.io/­heroicdocs.singlestore.com
DeveloperDatabricksSpotifySingleStore Inc.
Initial release201320142013
Current release8.5, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree developer edition available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Go
Server operating systemshostedLinux info64 bit version required
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyes
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 indexesyesyes infovia Elasticsearchyes
SQL infoSupport of SQLwith Databricks SQLnoyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesPython
R
Scala
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlFine grained access control via users, groups and roles
More information provided by the system vendor
DatabricksHeroicSingleStore infoformer name was MemSQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHeroicSingleStore infoformer name was MemSQL
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Recent citations in the news

Databricks says with its new Databricks Apps platform, you can build tailored enterprise apps in 5 minutes
8 October 2024, InfoWorld

With Databricks Apps, business users get more out of data
8 October 2024, Techzine Europe

Treasure Data Announces Availability of Live Connect, Its Enterprise Zero-Copy Solution, for the Databricks Data Intelligence Platform
8 October 2024, businesswire.com

Databricks sues patent holders over alleged 'extortion' scheme
9 September 2024, Reuters

Snowflake, Databricks back $20M round for AI data management startup Voyage AI
3 October 2024, SiliconANGLE News

provided by Google News

How Code Wizards load tested Heroic Labs’ Nakama to two million concurrent players with AWS
1 October 2024, AWS Blog

provided by Google News

SingleStore acquires BryteFlow to boost data ingestion capabilities
3 October 2024, InfoWorld

SingleStore acquires BryteFlow to better digest ERP and CRM data
4 October 2024, Blocks & Files

SingleStore Acquires BryteFlow ​​to Accelerate Adoption of Real-Time Analytics, GenAI
3 October 2024, Business Wire

SingleStore's BryteFlow acquisition targets data integration
3 October 2024, TechTarget

Third time was the charm for SingleStore in the cloud, CEO says
8 July 2024, The Register

provided by Google News



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