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DBMS > CrateDB vs. etcd vs. Firebolt vs. GBase

System Properties Comparison CrateDB vs. etcd vs. Firebolt vs. GBase

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonetcd  Xexclude from comparisonFirebolt  Xexclude from comparisonGBase  Xexclude from comparison
DescriptionDistributed Database based on LuceneA distributed reliable key-value storeHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeRelational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score1.90
Rank#134  Overall
#62  Relational DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Websitecratedb.cometcd.io
github.com/­etcd-io/­etcd
www.firebolt.iowww.gbase.cn
Technical documentationcratedb.com/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.firebolt.io
DeveloperCrateFirebolt Analytics Inc.General Data Technology Co., Ltd.
Initial release201320202004
Current release3.4, August 2019GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2.0commercialcommercial
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 languageJavaGoC, Java, Python
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
Windows infoexperimental
hostedLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyesStandard with numerous extensions
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC
JSON over HTTP
.Net
ODBC
RESTful HTTP API
ADO.NET
C API
JDBC
ODBC
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++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
JavaScript (Node.js)
Python
C#
Server-side scripts infoStored proceduresuser defined functions (Javascript)nonouser defined functions
Triggersnoyes, watching key changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.depending on storage layeryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
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 strategynoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlrights management via user accountsnoyes
More information provided by the system vendor
CrateDBetcdFireboltGBase
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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CrateDBetcdFireboltGBase
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