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DBMS > GridDB vs. Hazelcast vs. HEAVY.AI vs. SwayDB

System Properties Comparison GridDB vs. Hazelcast vs. HEAVY.AI vs. SwayDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data gridA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelTime Series DBMSKey-value storeRelational DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitegriddb.nethazelcast.comgithub.com/­heavyai/­heavydb
www.heavy.ai
swaydb.simer.au
Technical documentationdocs.griddb.nethazelcast.org/­imdg/­docsdocs.heavy.ai
DeveloperToshiba CorporationHazelcastHEAVY.AI, Inc.Simer Plaha
Initial release2013200820162018
Current release5.1, August 20225.3.6, November 20235.10, January 2022
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++ and CUDAScala
Server operating systemsLinuxAll OS with a Java VMLinux
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesno
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.noyes infothe object must implement a serialization strategynono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageyesno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesnono
Triggersyesyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoRound robinnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelone or two-phase-commit; repeatable reads; read commitednoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseRole-based access controlfine grained access rights according to SQL-standardno
More information provided by the system vendor
GridDBHazelcastHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022SwayDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» 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

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More resources
GridDBHazelcastHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022SwayDB
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