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DBMS > Amazon Neptune vs. CrateDB vs. Ehcache vs. Lovefield

System Properties Comparison Amazon Neptune vs. CrateDB vs. Ehcache vs. Lovefield

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCrateDB  Xexclude from comparisonEhcache  Xexclude from comparisonLovefield  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudDistributed Database based on LuceneA widely adopted Java cache with tiered storage optionsEmbeddable relational database for web apps written in pure JavaScript
Primary database modelGraph DBMS
RDF store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score0.29
Rank#293  Overall
#133  Relational DBMS
Websiteaws.amazon.com/­neptunecratedb.comwww.ehcache.orggoogle.github.io/­lovefield
Technical documentationaws.amazon.com/­neptune/­developer-resourcescratedb.com/­docswww.ehcache.org/­documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperAmazonCrateTerracotta Inc, owned by Software AGGoogle
Initial release2017201320092014
Current release3.10.0, March 20222.1.12, February 2017
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
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 languageJavaJavaJavaScript
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesnoyesnoyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like query language infovia JavaScript builder pattern
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JCache
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.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
JavaJavaScript
Server-side scripts infoStored proceduresnouser defined functions (Javascript)nono
Triggersnonoyes infoCache Event ListenersUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoby using Terracotta Servernone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Configurable replication on table/partition-levelyes infoby using Terracotta Servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Tunable Consistency (Strong, Eventual, Weak)
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyyes infosupports JTA and can work as an XA resourceACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infousing a tiered cache-storage approachyes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDB
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)rights management via user accountsnono
More information provided by the system vendor
Amazon NeptuneCrateDBEhcacheLovefield
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
Amazon NeptuneCrateDBEhcacheLovefield
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