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DBMS > BoltDB vs. CrateDB vs. Google Cloud Bigtable vs. MonetDB

System Properties Comparison BoltDB vs. CrateDB vs. Google Cloud Bigtable vs. MonetDB

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonCrateDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMonetDB  Xexclude from comparison
DescriptionAn embedded key-value store for Go.Distributed Database based on LuceneGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A relational database management system that stores data in columns
Primary database modelKey-value storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.72
Rank#145  Overall
#67  Relational DBMS
Websitegithub.com/­boltdb/­boltcratedb.comcloud.google.com/­bigtablewww.monetdb.org
Technical documentationcratedb.com/­docscloud.google.com/­bigtable/­docswww.monetdb.org/­Documentation
DeveloperCrateGoogleMonetDB BV
Initial release2013201320152004
Current releaseDec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen SourcecommercialOpen Source infoMozilla Public License 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 languageGoJavaC
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedFreeBSD
Linux
OS X
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitynoyes infoSQL 2003 with some extensions
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesGo.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)
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresnouser defined functions (Javascript)noyes, in SQL, C, R
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesnoneConfigurable replication on table/partition-levelInternal replication in Colossus, and regional replication between two clusters in different zonesnone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Read-after-write consistency on record level
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesno infounique row identifiers can be used for implementing an optimistic concurrency control strategyAtomic single-row operationsACID
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.nonono
User concepts infoAccess controlnorights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard
More information provided by the system vendor
BoltDBCrateDBGoogle Cloud BigtableMonetDB
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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More resources
BoltDBCrateDBGoogle Cloud BigtableMonetDB
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