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DBMS > Ehcache vs. RavenDB vs. SWC-DB vs. Vertica

System Properties Comparison Ehcache vs. RavenDB vs. SWC-DB vs. Vertica

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonRavenDB  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA high performance, scalable Wide Column DBMSCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelKey-value storeDocument storeWide column storeRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Time Series DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.23
Rank#68  Overall
#8  Key-value stores
Score3.01
Rank#101  Overall
#17  Document stores
Score0.01
Rank#387  Overall
#13  Wide column stores
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitewww.ehcache.orgravendb.netgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
www.vertica.com
Technical documentationwww.ehcache.org/­documentationravendb.net/­docsvertica.com/­documentation
DeveloperTerracotta Inc, owned by Software AGHibernating RhinosAlex KashirinOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2009201020202005
Current release3.10.0, March 20225.4, July 20220.5, April 202112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoAGPL version 3, commercial license availableOpen Source infoGPL V3commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#C++C++
Server operating systemsAll OS with a Java VMLinux
macOS
Raspberry Pi
Windows
LinuxLinux
Data schemeschema-freeschema-freeschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesnoyes
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 indexesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query language (RQL)SQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJCache.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Proprietary protocol
Thrift
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoCache Event Listenersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerMulti-source replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnoAuthorization levels configured per client per databasefine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EhcacheRavenDBSWC-DB infoSuper Wide Column DatabaseVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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EhcacheRavenDBSWC-DB infoSuper Wide Column DatabaseVertica infoOpenText™ Vertica™
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