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DBMS > Blazegraph vs. Databricks vs. Hawkular Metrics vs. HugeGraph vs. TimescaleDB

System Properties Comparison Blazegraph vs. Databricks vs. Hawkular Metrics vs. HugeGraph vs. TimescaleDB

Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonDatabricks  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHugeGraph  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A fast-speed and highly-scalable Graph DBMSA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Time Series DBMSGraph DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteblazegraph.comwww.databricks.comwww.hawkular.orggithub.com/­hugegraph
hugegraph.apache.org
www.timescale.com
Technical documentationwiki.blazegraph.comdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehugegraph.apache.org/­docsdocs.timescale.com
DeveloperBlazegraphDatabricksCommunity supported by Red HatBaiduTimescale
Initial release20062013201420182017
Current release2.1.5, March 20190.92.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
Linux
macOS
Unix
Linux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesnonoyes
Secondary indexesyesyesnoyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLSPARQL is used as query languagewith Databricks SQLnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
ODBC
RESTful HTTP API
HTTP RESTJava API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Python
R
Scala
Go
Java
Python
Ruby
Groovy
Java
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesnoasynchronous Gremlin script jobsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrayes infodepending on used storage backend, e.g. Cassandra and HBaseyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesselectable replication factor infobased on Cassandrayes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonovia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsnoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)noUsers, roles and permissionsfine grained access rights according to SQL-standard
More information provided by the system vendor
BlazegraphDatabricksHawkular MetricsHugeGraphTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BlazegraphDatabricksHawkular MetricsHugeGraphTimescaleDB
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