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DBMS > CrateDB vs. Ehcache vs. etcd vs. FeatureBase

System Properties Comparison CrateDB vs. Ehcache vs. etcd vs. FeatureBase

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEhcache  Xexclude from comparisonetcd  Xexclude from comparisonFeatureBase  Xexclude from comparison
DescriptionDistributed Database based on LuceneA widely adopted Java cache with tiered storage optionsA distributed reliable key-value storeReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeKey-value storeRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.31
Rank#292  Overall
#135  Relational DBMS
Websitecratedb.comwww.ehcache.orgetcd.io
github.com/­etcd-io/­etcd
www.featurebase.com
Technical documentationcratedb.com/­docswww.ehcache.org/­documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.featurebase.com
DeveloperCrateTerracotta Inc, owned by Software AGMolecula and Pilosa Open Source Contributors
Initial release201320092017
Current release3.10.0, March 20223.4, August 20192022, May 2022
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0commercial
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 languageJavaJavaGoGo
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesnonono
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynonoSQL queries
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JCachegRPC
JSON over HTTP
gRPC
JDBC
Kafka Connector
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
Java.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)nono
Triggersnoyes infoCache Event Listenersyes, watching key changesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoby using Terracotta ServerSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes infoby using Terracotta ServerUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Tunable Consistency (Strong, Eventual, Weak)Immediate Consistency
Foreign keys infoReferential integritynononoyes
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 strategyyes infosupports JTA and can work as an XA resourcenoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes, using Linux fsync
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlrights management via user accountsnono
More information provided by the system vendor
CrateDBEhcacheetcdFeatureBase
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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CrateDBEhcacheetcdFeatureBase
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