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DBMS > GeoSpock vs. Spark SQL vs. STSdb vs. Tarantool vs. TDSQL for MySQL

System Properties Comparison GeoSpock vs. Spark SQL vs. STSdb vs. Tarantool vs. TDSQL for MySQL

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTarantool  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleSpark 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 applicationsA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelRelational DBMSRelational DBMSKey-value storeDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS infowith Tarantool/GIS extensionDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websitegeospock.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.tarantool.iowww.tencentcloud.com/­products/­dcdb
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tarantool.io/­en/­docwww.tencentcloud.com/­document/­product/­1042
DeveloperGeoSpockApache Software FoundationSTS Soft SCVKTencent
Initial release2014201120082013
Current release2.0, September 20193.5.0 ( 2.13), September 20234.0.8, September 20152.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptScalaC#C and C++
Server operating systemshostedLinux
OS X
Windows
WindowsBSD
Linux
macOS
hosted
Data schemeyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesyes infoprimitive types and user defined types (classes)string, double, decimal, uuid, integer, blob, boolean, datetimeyes
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 indexestemporal, categoricalnonoyesyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)SQL-like DML and DDL statementsnoFull-featured ANSI SQL supportyes
APIs and other access methodsJDBCJDBC
ODBC
.NET Client APIOpen binary protocolJDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C#
Java
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresnononoLua, C and SQL stored proceduresyes
Triggersnononoyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingyes, utilizing Spark CorenoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Automatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyesyes, write ahead loggingyes
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 persistenceno
User concepts infoAccess controlAccess rights for users can be defined per tablenonoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Users with fine-grained authorization concept

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More resources
GeoSpockSpark SQLSTSdbTarantoolTDSQL for MySQL
DB-Engines blog posts

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

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