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DBMS > Apache Druid vs. Linter vs. ObjectBox vs. Tarantool

System Properties Comparison Apache Druid vs. Linter vs. ObjectBox vs. Tarantool

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonLinter  Xexclude from comparisonObjectBox  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataRDBMS for high security requirementsExtremely 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 modelRelational DBMS
Time Series DBMS
Relational DBMSObject oriented DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMSTime Series DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitedruid.apache.orglinter.ruobjectbox.iowww.tarantool.io
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.objectbox.iowww.tarantool.io/­en/­doc
DeveloperApache Software Foundation and contributorsrelex.ruObjectBox LimitedVK
Initial release2012199020172008
Current release29.0.1, April 20242.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen 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

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Implementation languageJavaC and C++C and C++C and C++
Server operating systemsLinux
OS X
Unix
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Android
iOS
Linux
macOS
Windows
BSD
Linux
macOS
Data schemeyes infoschema-less columns are supportedyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, 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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingyesnoFull-featured ANSI SQL support
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Proprietary native APIOpen binary protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
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 proceduresnoyes infoproprietary syntax with the possibility to convert from PL/SQLnoLua, C and SQL stored procedures
Triggersnoyesnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednonenoneSharding, 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, via HDFS, S3 or other storage enginesSource-replica replicationonline/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 methodsnonono
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 integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID, 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 persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardyesAccess 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
Apache DruidLinterObjectBoxTarantool
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More resources
Apache DruidLinterObjectBoxTarantool
DB-Engines blog posts

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

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