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DBMS > GridGain vs. LevelDB vs. ObjectBox vs. Tarantool

System Properties Comparison GridGain vs. LevelDB vs. ObjectBox vs. Tarantool

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonLevelDB  Xexclude from comparisonObjectBox  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesExtremely fast embedded database for small devices, IoT and MobileIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelKey-value store
Relational DBMS
Key-value storeObject oriented DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitewww.gridgain.comgithub.com/­google/­leveldbobjectbox.iowww.tarantool.io
Technical documentationwww.gridgain.com/­docs/­index.htmlgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.objectbox.iowww.tarantool.io/­en/­doc
DeveloperGridGain Systems, Inc.GoogleObjectBox LimitedVK
Initial release2007201120172008
Current releaseGridGain 8.5.11.23, February 20212.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoApache License 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
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 languageJava, C++, .NetC++C and C++C and C++
Server operating systemsLinux
OS X
Solaris
Windows
Illumos
Linux
OS X
Windows
Android
iOS
Linux
macOS
Windows
BSD
Linux
macOS
Data schemeyesschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesnoyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.yesnonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnonoFull-featured ANSI SQL support
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary native APIOpen binary protocol
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nonoLua, C and SQL stored procedures
Triggersyes (cache interceptors and events)nonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)noneonline/offline synchronization between client and serverAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlSecurity Hooks for custom implementationsnoyesAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
More information provided by the system vendor
GridGainLevelDBObjectBoxTarantool
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More resources
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DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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