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DBMS > CrateDB vs. Google Cloud Bigtable vs. Graphite vs. Prometheus

System Properties Comparison CrateDB vs. Google Cloud Bigtable vs. Graphite vs. Prometheus

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraphite  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionDistributed 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.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperOpen-source Time Series DBMS and monitoring system
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Wide column store
Time Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score4.75
Rank#75  Overall
#5  Time Series DBMS
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Websitecratedb.comcloud.google.com/­bigtablegithub.com/­graphite-project/­graphite-webprometheus.io
Technical documentationcratedb.com/­docscloud.google.com/­bigtable/­docsgraphite.readthedocs.ioprometheus.io/­docs
DeveloperCrateGoogleChris Davis
Initial release2013201520062015
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 languageJavaPythonGo
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinux
Unix
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesnoNumeric data onlyNumeric data only
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 infoImport of XML data possible
Secondary indexesyesnonono
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynonono
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)
HTTP API
Sockets
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)
Python
JavaScript (Node.js)
Python
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)nonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelInternal replication in Colossus, and regional replication between two clusters in different zonesnoneyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)nonenone
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 strategyAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infolockingyes
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 controlrights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono
More information provided by the system vendor
CrateDBGoogle Cloud BigtableGraphitePrometheus
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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CrateDBGoogle Cloud BigtableGraphitePrometheus
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