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DBMS > Apache IoTDB vs. EXASOL vs. Spark SQL vs. STSdb vs. Tarantool

System Properties Comparison Apache IoTDB vs. EXASOL vs. Spark SQL vs. STSdb vs. Tarantool

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEXASOL  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Spark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelTime Series DBMSRelational DBMSRelational DBMSKey-value storeDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteiotdb.apache.orgwww.exasol.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.tarantool.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.exasol.com/­resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tarantool.io/­en/­doc
DeveloperApache Software FoundationExasolApache Software FoundationSTS Soft SCVK
Initial release20182000201420112008
Current release1.1.0, April 20233.5.0 ( 2.13), September 20234.0.8, September 20152.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC#C and C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
WindowsBSD
Linux
macOS
Data schemeyesyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)string, 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 indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like query languageyesSQL-like DML and DDL statementsnoFull-featured ANSI SQL support
APIs and other access methodsJDBC
Native API
.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
.NET Client APIOpen binary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
Lua
Python
R
Java
Python
R
Scala
C#
Java
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesuser defined functionsnonoLua, C and SQL stored procedures
Triggersyesyesnonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingyes, utilizing Spark CorenoneSharding, 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 nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnonenoneAsynchronous 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 methodsIntegration with Hadoop and Sparkyes infoHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate 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 integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlyesAccess rights for users, groups and roles according to SQL-standardnonoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
Apache IoTDBEXASOLSpark SQLSTSdbTarantool
DB-Engines blog posts

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

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