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DBMS > Ehcache vs. NSDb vs. Sadas Engine vs. Vertica

System Properties Comparison Ehcache vs. NSDb vs. Sadas Engine vs. Vertica

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonNSDb  Xexclude from comparisonSadas Engine  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environmentsCloud or on-premises 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 storeTime Series DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.47
Rank#66  Overall
#9  Key-value stores
Score0.00
Rank#354  Overall
#33  Time Series DBMS
Score0.00
Rank#354  Overall
#152  Relational DBMS
Score19.29
Rank#38  Overall
#24  Relational DBMS
Websitewww.ehcache.orgnsdb.iowww.sadasengine.comwww.vertica.com
Technical documentationwww.ehcache.org/­documentationnsdb.io/­Architecturewww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbvertica.com/­documentation
DeveloperTerracotta Inc, owned by Software AGSADAS s.r.l.Micro Focus infoprior to that Hewlett Packard
Initial release2009201720062005
Current release3.9.6, September 20218.011.1, February 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0commercial infofree trial version availablecommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.
Implementation languageJavaJava, ScalaC++C++
Server operating systemsAll OS with a Java VMLinux
macOS
AIX
Linux
Windows
Linux
Data schemeschema-freeyesyes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyesyes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY
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 indexesnoall fields are automatically indexedyesNo Indexes Required
SQL infoSupport of SQLnoSQL-like query languageyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJCachegRPC
HTTP REST
WebSocket
JDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaJava
Scala
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnononoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoCache Event Listenersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardinghorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServernoneMulti-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 methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EhcacheNSDbSadas EngineVertica infoVertica Analytics Platform
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more
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...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
EhcacheNSDbSadas EngineVertica infoVertica Analytics Platform
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