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DBMS > Blueflood vs. Brytlyt vs. Google Cloud Datastore vs. Kinetica vs. Titan

System Properties Comparison Blueflood vs. Brytlyt vs. Google Cloud Datastore vs. Kinetica vs. Titan

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonBrytlyt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionScalable TimeSeries DBMS based on CassandraScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelTime Series DBMSRelational DBMSDocument storeRelational DBMSGraph DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websiteblueflood.iobrytlyt.iocloud.google.com/­datastorewww.kinetica.comgithub.com/­thinkaurelius/­titan
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.brytlyt.iocloud.google.com/­datastore/­docsdocs.kinetica.comgithub.com/­thinkaurelius/­titan/­wiki
DeveloperRackspaceBrytlytGoogleKineticaAurelius, owned by DataStax
Initial release20132016200820122012
Current release5.0, August 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++ and CUDAC, C++Java
Server operating systemsLinux
OS X
Linux
OS X
Windows
hostedLinuxLinux
OS X
Unix
Windows
Data schemepredefined schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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 infospecific XML-type available, but no XML query functionality.nono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsHTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Clojure
Java
Python
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLusing Google App Engineuser defined functionsyes
TriggersnoyesCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationMulti-source replication using PaxosSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate 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 or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAM
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)Access rights for users and roles on table levelUser authentification and security via Rexster Graph Server

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More resources
BluefloodBrytlytGoogle Cloud DatastoreKineticaTitan
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