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DBMS > Amazon CloudSearch vs. Apache Impala vs. Postgres-XL vs. Tarantool

System Properties Comparison Amazon CloudSearch vs. Apache Impala vs. Postgres-XL vs. Tarantool

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonApache Impala  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudAnalytic DBMS for HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelSearch engineRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#137  Overall
#12  Search engines
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteaws.amazon.com/­cloudsearchimpala.apache.orgwww.postgres-xl.orgwww.tarantool.io
Technical documentationdocs.aws.amazon.com/­cloudsearchimpala.apache.org/­impala-docs.htmlwww.postgres-xl.org/­documentationwww.tarantool.io/­en/­doc
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaVK
Initial release201220132014 infosince 2012, originally named StormDB2008
Current release4.1.0, June 202210 R1, October 20182.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoMozilla public licenseOpen 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++CC and C++
Server operating systemshostedLinuxLinux
macOS
BSD
Linux
macOS
Data schemeyesyesyesFlexible 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.noyes infoXML type, but no XML query functionalityno
Secondary indexesyes infoall search fields are automatically indexedyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infodistributed, parallel query executionFull-featured ANSI SQL support
APIs and other access methodsHTTP APIJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Open binary protocol
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functionsLua, C and SQL stored procedures
Triggersnonoyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardinghorizontal partitioningSharding, 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 infomanaged transparently by AWSselectable replication factorAsynchronous 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 infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 datanonoACID infoMVCCACID, 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 controlauthentication via encrypted signaturesAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess 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 CloudSearchApache ImpalaPostgres-XLTarantool
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