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DBMS > Apache Druid vs. Blazegraph vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. RavenDB

System Properties Comparison Apache Druid vs. Blazegraph vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. RavenDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBlazegraph  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRavenDB  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsFully managed big data interactive analytics platformOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMS
Time Series DBMS
Graph DBMS
RDF store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infocolumn orientedDocument store
Secondary database modelsGraph DBMS
Search engine
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Graph DBMS
Spatial DBMS
Time Series 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
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitedruid.apache.orgblazegraph.comwww.gigaspaces.comazure.microsoft.com/­services/­data-explorerravendb.net
Technical documentationdruid.apache.org/­docs/­latest/­designwiki.blazegraph.comdocs.gigaspaces.com/­latest/­landing.htmldocs.microsoft.com/­en-us/­azure/­data-explorerravendb.net/­docs
DeveloperApache Software Foundation and contributorsBlazegraphGigaspaces TechnologiesMicrosoftHibernating Rhinos
Initial release20122006200020192010
Current release29.0.1, April 20242.1.5, March 201915.5, September 2020cloud service with continuous releases5.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoextended commercial license availableOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava, C++, .NetC#
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
Linux
macOS
Solaris
Windows
hostedLinux
macOS
Raspberry Pi
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nono infoXML can be used for describing objects metadatayes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL for queryingSPARQL is used as query languageSQL-99 for query and DML statementsKusto Query Language (KQL), SQL subsetSQL-like query language (RQL)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyesyesYes, possible languages: KQL, Python, Ryes
Triggersnonoyes, event driven architectureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoMap-Reduce pattern can be built with XAP task executorsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyes infoRelationships in Graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID, Cluster-wide transaction available
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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity and Authentication via Web Application Container (Tomcat, Jetty)Role-based access controlAzure Active Directory AuthenticationAuthorization levels configured per client per database

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More resources
Apache DruidBlazegraphGigaSpacesMicrosoft Azure Data ExplorerRavenDB
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