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DBMS > Brytlyt vs. Google Cloud Datastore vs. Sphinx vs. VelocityDB

System Properties Comparison Brytlyt vs. Google Cloud Datastore vs. Sphinx vs. VelocityDB

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSphinx  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen source search engine for searching in data from different sources, e.g. relational databasesA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelRelational DBMSDocument storeSearch engineGraph DBMS
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#279  Overall
#126  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score6.03
Rank#60  Overall
#6  Search engines
Score0.11
Rank#347  Overall
#35  Graph DBMS
#15  Object oriented DBMS
Websitebrytlyt.iocloud.google.com/­datastoresphinxsearch.comvelocitydb.com
Technical documentationdocs.brytlyt.iocloud.google.com/­datastore/­docssphinxsearch.com/­docsvelocitydb.com/­UserGuide
DeveloperBrytlytGoogleSphinx Technologies Inc.VelocityDB Inc
Initial release2016200820012011
Current release5.0, August 20233.5.1, February 20237.x
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAC++C#
Server operating systemsLinux
OS X
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Any that supports .NET
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details herenoyes
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.yes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query language (SphinxQL)no
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocol.Net
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLusing Google App Enginenono
TriggersyesCallbacks using the Google Apps EnginenoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noBased on Windows Authentication

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BrytlytGoogle Cloud DatastoreSphinxVelocityDB
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