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DBMS > Brytlyt vs. InfinityDB vs. IRONdb vs. Spark SQL

System Properties Comparison Brytlyt vs. InfinityDB vs. IRONdb vs. Spark SQL

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonInfinityDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA Java embedded Key-Value Store which extends the Java Map interfaceA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#279  Overall
#126  Relational DBMS
Score0.07
Rank#359  Overall
#54  Key-value stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitebrytlyt.ioboilerbay.comwww.circonus.com/solutions/time-series-database/spark.apache.org/­sql
Technical documentationdocs.brytlyt.ioboilerbay.com/­infinitydb/­manualdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBrytlytBoiler Bay Inc.Circonus LLC.Apache Software Foundation
Initial release2016200220172014
Current release5.0, August 20234.0V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAJavaC and C++Scala
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinuxLinux
OS X
Windows
Data schemeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes infotext, numeric, histogramsyes
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.nonono
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilitynono
SQL infoSupport of SQLyesnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP APIJDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Java.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnoyes, in Luano
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic, metric affinity per nodeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesno infomanual creation possible, using inversions based on multi-value capabilitynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnono
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnonono

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More resources
BrytlytInfinityDBIRONdbSpark SQL
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