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DBMS > Apache Druid vs. Blazegraph vs. CrateDB vs. GigaSpaces vs. HEAVY.AI

System Properties Comparison Apache Druid vs. Blazegraph vs. CrateDB vs. GigaSpaces vs. HEAVY.AI

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBlazegraph  Xexclude from comparisonCrateDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  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.Distributed Database based on LuceneHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMS
Time Series DBMS
Graph DBMS
RDF store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsRelational DBMSGraph DBMS
Search engine
Spatial 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
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Websitedruid.apache.orgblazegraph.comcratedb.comwww.gigaspaces.comgithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdruid.apache.org/­docs/­latest/­designwiki.blazegraph.comcratedb.com/­docsdocs.gigaspaces.com/­latest/­landing.htmldocs.heavy.ai
DeveloperApache Software Foundation and contributorsBlazegraphCrateGigaspaces TechnologiesHEAVY.AI, Inc.
Initial release20122006201320002016
Current release29.0.1, April 20242.1.5, March 201915.5, September 20205.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoextended commercial license availableOpen SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenonononono
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 languageJavaJavaJavaJava, C++, .NetC++ and CUDA
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
macOS
Solaris
Windows
Linux
Data schemeyes infoschema-less columns are supportedschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesyesyes
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.nonono infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL for queryingSPARQL is used as query languageyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-99 for query and DML statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Vega
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.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
.Net
C++
Java
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresnoyesuser defined functions (Javascript)yesno
Triggersnononoyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesConfigurable replication on table/partition-levelMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Read-after-write consistency on record level
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in Graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDno
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.nonoyesyes
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)rights management via user accountsRole-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidBlazegraphCrateDBGigaSpacesHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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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Apache DruidBlazegraphCrateDBGigaSpacesHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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