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DBMS > Realm vs. SingleStore vs. TypeDB

System Properties Comparison Realm vs. SingleStore vs. TypeDB

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Editorial information provided by DB-Engines
NameRealm  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataMySQL 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 typeTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelDocument storeRelational DBMSGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.60
Rank#52  Overall
#9  Document stores
Score5.60
Rank#62  Overall
#35  Relational DBMS
Score0.65
Rank#234  Overall
#20  Graph DBMS
#107  Relational DBMS
Websiterealm.iowww.singlestore.comtypedb.com
Technical documentationrealm.io/­docsdocs.singlestore.comtypedb.com/­docs
DeveloperRealm, acquired by MongoDB in May 2019SingleStore Inc.Vaticle
Initial release201420132016
Current release8.5, January 20242.26.3, January 2024
License infoCommercial or Open SourceOpen Sourcecommercial infofree developer edition availableOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageC++, GoJava
Server operating systemsAndroid
Backend: server-less
iOS
Windows
Linux info64 bit version requiredLinux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoyes infobut no triggers and foreign keysno
APIs and other access methodsCluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languages.Net
Java infowith Android only
Objective-C
React Native
Swift
Bash
C
C#
Java
JavaScript (Node.js)
Python
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresno inforuns within the applications so server-side scripts are unnecessaryyesno
Triggersyes infoChange Listenersnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infohash partitioningSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infostores two copies of each physical data partition on two separate nodesMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan define user-defined aggregate functions for map-reduce-style calculationsyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoIn-Memory realmyesno
User concepts infoAccess controlyesFine grained access control via users, groups and rolesyes infoat REST API level; other APIs in progress
More information provided by the system vendor
RealmSingleStore infoformer name was MemSQLTypeDB infoformerly named Grakn
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
TypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Life sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more
Apache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
RealmSingleStore infoformer name was MemSQLTypeDB infoformerly named Grakn
DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022,  Akmal Chaudhri, SingleStore (sponsor) 

Cloud-Based Analytics With SingleStoreDB
9 June 2022,  Akmal Chaudhri, SingleStore (sponsor) 

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

show all

Recent citations in the news

GDG North Jersey's February Meeting Covers Realm, A New Mobile Database
6 March 2016, njtechweekly.com

Danish CEO explains Silicon Valley learning curve for European entrepreneurs - San Francisco Business Times
6 October 2016, The Business Journals

MongoDB aims to unify developer experience with launch of MongoDB Cloud
9 June 2020, diginomica

Is Swift the Future of Server-side Development?
12 September 2017, Solutions Review

Kotlin Programming Language Will Surpass Java On Android Next Year
15 October 2017, Fossbytes

provided by Google News

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development
24 January 2024, Business Wire

SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files
29 January 2024, Blocks & Files

Leveraging SingleStoreDB Cloud Private Connectivity Using AWS PrivateLink | Amazon Web Services
6 December 2023, AWS Blog

Announcing watsonx.ai and SingleStore for generative AI applications
15 November 2023, IBM

provided by Google News

An Enterprise Data Stack Using TypeDB | by Daniel Crowe
2 September 2021, Towards Data Science

Speedb Goes Open Source With Its Speedb Data Engine, A Drop-in Replacement for RocksDB
9 November 2022, Business Wire

Modelling Biomedical Data for a Drug Discovery Knowledge Graph
6 October 2020, Towards Data Science

195 Data Science Libraries You Should Reconsider Using | by Dimitris Effrosynidis
2 February 2024, DataDrivenInvestor

How Roche Discovered Novel Potential Gene Targets with TypeDB
8 June 2021, Towards Data Science

provided by Google News



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