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DBMS > Apache Druid vs. Google Cloud Datastore vs. Hawkular Metrics vs. HugeGraph

System Properties Comparison Apache Druid vs. Google Cloud Datastore vs. Hawkular Metrics vs. HugeGraph

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular 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 DBMS
Primary database modelRelational DBMS
Time Series DBMS
Document storeTime Series DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitedruid.apache.orgcloud.google.com/­datastorewww.hawkular.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidehugegraph.apache.org/­docs
DeveloperApache Software Foundation and contributorsGoogleCommunity supported by Red HatBaidu
Initial release2012200820142018
Current release29.0.1, April 20240.9
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
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 languageJavaJavaJava
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Windows
Linux
macOS
Unix
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, 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.nononono
Secondary indexesyesyesnoyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL for queryingSQL-like query language (GQL)nono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJava API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
Groovy
Java
Python
Server-side scripts infoStored proceduresnousing Google App Enginenoasynchronous Gremlin script jobs
TriggersnoCallbacks using the Google Apps Engineyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infobased on Cassandrayes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownovia hugegraph-spark
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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUsers, roles and permissions

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More resources
Apache DruidGoogle Cloud DatastoreHawkular MetricsHugeGraph
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