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DBMS > Hazelcast vs. Spark SQL vs. Sqrrl vs. TimescaleDB

System Properties Comparison Hazelcast vs. Spark SQL vs. Sqrrl vs. TimescaleDB

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparisonSqrrl  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionA widely adopted in-memory data gridSpark SQL is a component on top of 'Spark Core' for structured data processingAdaptable, secure NoSQL built on Apache AccumuloA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value storeRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Time Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitehazelcast.comspark.apache.org/­sqlsqrrl.comwww.timescale.com
Technical documentationhazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperHazelcastApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.Timescale
Initial release2008201420122017
Current release5.3.6, November 20233.5.0 ( 2.13), September 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaJavaC
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 infothe object must implement a serialization strategynoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes infoEventsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding infomaking use of Hadoopyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapnoneselectable replication factor infomaking use of HadoopSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoAtomic updates per row, document, or graph entityACID
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.yesnono
User concepts infoAccess controlRole-based access controlnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)fine grained access rights according to SQL-standard

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More resources
HazelcastSpark SQLSqrrlTimescaleDB
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