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DBMS > CrateDB vs. Dgraph vs. Hazelcast vs. Solr

System Properties Comparison CrateDB vs. Dgraph vs. Hazelcast vs. Solr

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonDgraph  Xexclude from comparisonHazelcast  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionDistributed Database based on LuceneDistributed and scalable native Graph DBMSA widely adopted in-memory data gridA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Graph DBMSKey-value storeSearch engine
Secondary database modelsRelational DBMSDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitecratedb.comdgraph.iohazelcast.comsolr.apache.org
Technical documentationcratedb.com/­docsdgraph.io/­docshazelcast.org/­imdg/­docssolr.apache.org/­resources.html
DeveloperCrateDgraph Labs, Inc.HazelcastApache Software Foundation
Initial release2013201620082006
Current release5.3.6, November 20239.6.0, April 2024
License infoCommercial or Open SourceOpen SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2
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 languageJavaGoJavaJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Windows
All OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nonoyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languages.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
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyes infoEvent Listeners, Executor ServicesJava plugins
Triggersnonoyes infoEventsyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingyesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSynchronous replication via Raftyes infoReplicated Mapyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDone or two-phase-commit; repeatable reads; read commitedoptimistic locking
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.noyesyes
User concepts infoAccess controlrights management via user accountsno infoPlanned for future releasesRole-based access controlyes
More information provided by the system vendor
CrateDBDgraphHazelcastSolr
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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CrateDBDgraphHazelcastSolr
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