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DBMS > CrateDB vs. etcd vs. Hive vs. TinkerGraph

System Properties Comparison CrateDB vs. etcd vs. Hive vs. TinkerGraph

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonetcd  Xexclude from comparisonHive  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionDistributed Database based on LuceneA distributed reliable key-value storedata warehouse software for querying and managing large distributed datasets, built on HadoopA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeRelational DBMSGraph 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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitecratedb.cometcd.io
github.com/­etcd-io/­etcd
hive.apache.orgtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationcratedb.com/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperCrateApache Software Foundation infoinitially developed by Facebook
Initial release201320122009
Current release3.4, August 20193.1.3, April 2022
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
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 languageJavaGoJavaJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
Windows infoexperimental
All OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
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.nonono
Secondary indexesyesnoyesno
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC
JSON over HTTP
JDBC
ODBC
Thrift
TinkerPop 3
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
C++
Java
PHP
Python
Groovy
Java
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyes infouser defined functions and integration of map-reduceno
Triggersnoyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
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.selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistencynone
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
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 strategynonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesno
Durability infoSupport for making data persistentyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlrights management via user accountsnoAccess rights for users, groups and rolesno
More information provided by the system vendor
CrateDBetcdHiveTinkerGraph
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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