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DBMS > BigObject vs. CrateDB vs. Microsoft Azure Table Storage vs. openGemini

System Properties Comparison BigObject vs. CrateDB vs. Microsoft Azure Table Storage vs. openGemini

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCrateDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonopenGemini  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesDistributed Database based on LuceneA Wide Column Store for rapid development using massive semi-structured datasetsAn open source distributed Time Series DBMS with high concurrency, high performance, and high scalability
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Wide column storeTime Series DBMS
Secondary database modelsRelational DBMS
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
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.01
Rank#375  Overall
#39  Time Series DBMS
Websitebigobject.iocratedb.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.opengemini.org
github.com/­openGemini
Technical documentationdocs.bigobject.iocratedb.com/­docsdocs.opengemini.org/­guide
DeveloperBigObject, Inc.CrateMicrosoftHuawei and openGemini community
Initial release2015201320122022
Current release1.1, July 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen SourcecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
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 languageJavaGo
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 supporthostedLinux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesInteger, Float, Boolean, String
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
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like query language
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP APIHTTP REST
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
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresLuauser defined functions (Javascript)nono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneConfigurable replication on table/partition-levelyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
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 Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonono
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 strategyoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesnonoyes
User concepts infoAccess controlnorights management via user accountsAccess rights based on private key authentication or shared access signaturesAdministrators and common users accounts
More information provided by the system vendor
BigObjectCrateDBMicrosoft Azure Table StorageopenGemini
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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BigObjectCrateDBMicrosoft Azure Table StorageopenGemini
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