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DBMS > Amazon SimpleDB vs. EsgynDB vs. Spark SQL vs. Tarantool

System Properties Comparison Amazon SimpleDB vs. EsgynDB vs. Spark SQL vs. Tarantool

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NameAmazon SimpleDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSpark SQL is a component on top of 'Spark Core' for structured data processingIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelKey-value storeRelational DBMSRelational DBMSDocument 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
Score1.85
Rank#138  Overall
#24  Key-value stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.esgyn.cnspark.apache.org/­sqlwww.tarantool.io
Technical documentationdocs.aws.amazon.com/­simpledbspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tarantool.io/­en/­doc
DeveloperAmazonEsgynApache Software FoundationVK
Initial release2007201520142008
Current release3.5.0 ( 2.13), September 20232.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaScalaC and C++
Server operating systemshostedLinuxLinux
OS X
Windows
BSD
Linux
macOS
Data schemeschema-freeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or datenoyesyesstring, 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.nonono
Secondary indexesyes infoAll columns are indexed automaticallyyesnoyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsFull-featured ANSI SQL support
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
JDBC
ODBC
Open binary protocol
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.NetJava
Python
R
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoJava Stored ProceduresnoLua, C and SQL stored procedures
Triggersnononoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingyes, utilizing Spark CoreSharding, 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 nodesyesMulti-source replication between multi datacentersnoneAsynchronous 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 methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
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 integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDnoACID, 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 controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardnoAccess 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
Amazon SimpleDBEsgynDBSpark SQLTarantool
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