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DBMS > Badger vs. Firebird vs. GridGain vs. Hazelcast vs. Sqrrl

System Properties Comparison Badger vs. Firebird vs. GridGain vs. Hazelcast vs. Sqrrl

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFirebird  Xexclude from comparisonGridGain  Xexclude from comparisonHazelcast  Xexclude from comparisonSqrrl  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.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Firebird is an open source RDBMS forked from Borland's InterBaseGridGain is an in-memory computing platform, built on Apache IgniteA widely adopted in-memory data gridAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeRelational DBMSKey-value store
Relational DBMS
Key-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score20.82
Rank#30  Overall
#18  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Websitegithub.com/­dgraph-io/­badgerwww.firebirdsql.orgwww.gridgain.comhazelcast.comsqrrl.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.firebirdsql.org/­en/­reference-manualswww.gridgain.com/­docs/­index.htmlhazelcast.org/­imdg/­docs
DeveloperDGraph LabsFirebird FoundationGridGain Systems, Inc.HazelcastAmazon infooriginally Sqrrl Data, Inc.
Initial release20172000 infoAs fork of Borland's InterBase200720082012
Current release5.0.0, January 2024GridGain 8.5.15.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoInitial Developer's Public LicensecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC and C++Java, C++, .NetJavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
Data schemeschema-freeyesyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesyesyes
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.noyesyes infothe object must implement a serialization strategy
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoyesANSI-99 for query and DML statements, subset of DDLSQL-like query languageno
APIs and other access methodsADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JCache
JPA
Memcached protocol
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGoC
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoPSQLyes (compute grid and cache interceptors can be used instead)yes infoEvent Listeners, Executor Servicesno
Triggersnoyesyes (cache interceptors and events)yes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationyes (replicated cache)yes infoReplicated Mapselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)yesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate 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.
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDone or two-phase-commit; repeatable reads; read commitedAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnoUsers with fine-grained authorization conceptSecurity Hooks for custom implementationsRole-based access controlCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
BadgerFirebirdGridGainHazelcastSqrrl
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