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DBMS > BoltDB vs. Datomic vs. Hazelcast vs. Spark SQL

System Properties Comparison BoltDB vs. Datomic vs. Hazelcast vs. Spark SQL

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDatomic  Xexclude from comparisonHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embedded key-value store for Go.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA widely adopted in-memory data gridSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSKey-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
Score0.74
Rank#220  Overall
#31  Key-value stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­boltdb/­boltwww.datomic.comhazelcast.comspark.apache.org/­sql
Technical documentationdocs.datomic.comhazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectHazelcastApache Software Foundation
Initial release2013201220082014
Current release1.0.6735, June 20235.3.6, November 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT Licensecommercial infolimited edition freeOpen Source infoApache Version 2; commercial licenses availableOpen 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 languageGoJava, ClojureJavaScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMAll OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnonoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGoClojure
Java
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes infoEvent Listeners, Executor Servicesno
TriggersnoBy using transaction functionsyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersyes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnonoRole-based access controlno

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More resources
BoltDBDatomicHazelcastSpark SQL
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