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DBMS > BigObject vs. CrateDB vs. InterSystems Caché vs. Realm

System Properties Comparison BigObject vs. CrateDB vs. InterSystems Caché vs. Realm

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCrateDB  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonRealm  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionAnalytic DBMS for real-time computations and queriesDistributed Database based on LuceneA multi-model DBMS and application serverA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Object oriented DBMS
Relational DBMS
Document store
Secondary database modelsRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Websitebigobject.iocratedb.comwww.intersystems.com/­products/­cacherealm.io
Technical documentationdocs.bigobject.iocratedb.com/­docsdocs.intersystems.comrealm.io/­docs
DeveloperBigObject, Inc.CrateInterSystemsRealm, acquired by MongoDB in May 2019
Initial release2015201319972014
Current release2018.1.4, May 2020
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen SourcecommercialOpen Source
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 languageJava
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Android
Backend: server-less
iOS
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)depending on used data modelyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, but no triggers and constraints, and PostgreSQL compatibilityyesno
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP 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++
Java
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresLuauser defined functions (Javascript)yesno inforuns within the applications so server-side scripts are unnecessary
Triggersnonoyesyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneConfigurable replication on table/partition-levelSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes
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.yesnoyesyes infoIn-Memory realm
User concepts infoAccess controlnorights management via user accountsAccess rights for users, groups and rolesyes
More information provided by the system vendor
BigObjectCrateDBInterSystems CachéRealm
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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