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DBMS > AlaSQL vs. Fujitsu Enterprise Postgres vs. Google Cloud Bigtable vs. Sphinx

System Properties Comparison AlaSQL vs. Fujitsu Enterprise Postgres vs. Google Cloud Bigtable vs. Sphinx

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Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionJavaScript DBMS libraryEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Wide column store
Search engine
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#256  Overall
#40  Document stores
#118  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.95
Rank#55  Overall
#5  Search engines
Websitealasql.orgwww.postgresql.fastware.comcloud.google.com/­bigtablesphinxsearch.com
Technical documentationgithub.com/­AlaSQL/­alasqlwww.postgresql.fastware.com/­product-manualscloud.google.com/­bigtable/­docssphinxsearch.com/­docs
DeveloperAndrey Gershun & Mathias R. WulffPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleSphinx Technologies Inc.
Initial release201420152001
Current releaseFujitsu Enterprise Postgres 14, January 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoMIT-LicensecommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptCC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Linux
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnono
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.nono
Secondary indexesnoyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.yesnoSQL-like query language (SphinxQL)
APIs and other access methodsJavaScript APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary protocol
Supported programming languagesJavaScript.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and by hashShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
AlaSQLFujitsu Enterprise PostgresGoogle Cloud BigtableSphinx
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
AlaSQLFujitsu Enterprise PostgresGoogle Cloud BigtableSphinx
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