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DBMS > Brytlyt vs. CrateDB vs. Datomic vs. HugeGraph

System Properties Comparison Brytlyt vs. CrateDB vs. Datomic vs. HugeGraph

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonCrateDB  Xexclude from comparisonDatomic  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLDistributed Database based on LuceneDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSGraph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websitebrytlyt.iocratedb.comwww.datomic.comgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationdocs.brytlyt.iocratedb.com/­docsdocs.datomic.comhugegraph.apache.org/­docs
DeveloperBrytlytCrateCognitectBaidu
Initial release2016201320122018
Current release5.0, August 20231.0.6735, June 20230.9
License infoCommercial or Open SourcecommercialOpen Sourcecommercial infolimited edition freeOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageC, C++ and CUDAJavaJava, ClojureJava
Server operating systemsLinux
OS X
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMLinux
macOS
Unix
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilitynono
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP APIJava API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Clojure
Java
Groovy
Java
Python
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLuser defined functions (Javascript)yes infoTransaction Functionsasynchronous Gremlin script jobs
TriggersyesnoBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationConfigurable replication on table/partition-levelnone infoBut extensive use of caching in the application peersyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyes
User concepts infoAccess controlfine grained access rights according to SQL-standardrights management via user accountsnoUsers, roles and permissions
More information provided by the system vendor
BrytlytCrateDBDatomicHugeGraph
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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