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DBMS > Brytlyt vs. Hazelcast vs. InterSystems IRIS vs. LevelDB vs. Splice Machine

System Properties Comparison Brytlyt vs. Hazelcast vs. InterSystems IRIS vs. LevelDB vs. Splice Machine

Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonHazelcast  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonLevelDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA widely adopted in-memory data gridA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value storeDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.54
Rank#84  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitebrytlyt.iohazelcast.comwww.intersystems.com/­products/­intersystems-irisgithub.com/­google/­leveldbsplicemachine.com
Technical documentationdocs.brytlyt.iohazelcast.org/­imdg/­docsdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsplicemachine.com/­how-it-works
DeveloperBrytlytHazelcastInterSystemsGoogleSplice Machine
Initial release20162008201820112014
Current release5.0, August 20235.3.6, November 20232023.3, June 20231.23, February 20213.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAJavaC++Java
Server operating systemsLinux
OS X
Windows
All OS with a Java VMAIX
Linux
macOS
Ubuntu
Windows
Illumos
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freedepending on used data modelschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.yes infospecific XML-type available, but no XML query functionality.yes infothe object must implement a serialization strategyyesno
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query languageyesnoyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C++
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLyes infoEvent Listeners, Executor Servicesyesnoyes infoJava
Triggersyesyes infoEventsyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlyesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
BrytlytHazelcastInterSystems IRISLevelDBSplice Machine
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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BrytlytHazelcastInterSystems IRISLevelDBSplice Machine
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