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DBMS > Apache Drill vs. Blueflood vs. CrateDB vs. Google Cloud Bigtable

System Properties Comparison Apache Drill vs. Blueflood vs. CrateDB vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonBlueflood  Xexclude from comparisonCrateDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageScalable TimeSeries DBMS based on CassandraDistributed 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.
Primary database modelDocument store
Relational DBMS
Time Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Wide column store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score0.06
Rank#353  Overall
#34  Time Series DBMS
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
Websitedrill.apache.orgblueflood.iocratedb.comcloud.google.com/­bigtable
Technical documentationdrill.apache.org/­docsgithub.com/­rax-maas/­blueflood/­wikicratedb.com/­docscloud.google.com/­bigtable/­docs
DeveloperApache Software FoundationRackspaceCrateGoogle
Initial release2012201320132015
Current release1.20.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
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 languageJavaJava
Server operating systemsLinux
OS X
Windows
Linux
OS X
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthosted
Data schemeschema-freepredefined schemeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesnonoyesno
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantnoyes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTADO.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)
Supported programming languagesC++.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
Server-side scripts infoStored proceduresuser defined functionsnouser defined functions (Javascript)no
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraConfigurable replication on table/partition-levelInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual 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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infounique row identifiers can be used for implementing an optimistic concurrency control strategyAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenonono
User concepts infoAccess controlDepending on the underlying data sourcenorights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
Apache DrillBluefloodCrateDBGoogle Cloud Bigtable
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
Apache DrillBluefloodCrateDBGoogle Cloud Bigtable
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