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DBMS > LeanXcale vs. Memcached vs. Vertica

System Properties Comparison LeanXcale vs. Memcached vs. Vertica

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Editorial information provided by DB-Engines
NameLeanXcale  Xexclude from comparisonMemcached  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesIn-memory key-value store, originally intended for cachingCloud 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 store
Relational DBMS
Key-value storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#297  Overall
#43  Key-value stores
#138  Relational DBMS
Score24.56
Rank#33  Overall
#4  Key-value stores
Score19.04
Rank#38  Overall
#24  Relational DBMS
Websitewww.leanxcale.comwww.memcached.orgwww.vertica.com
Technical documentationgithub.com/­memcached/­memcached/­wikivertica.com/­documentation
DeveloperLeanXcaleDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicro Focus infoprior to that Hewlett Packard
Initial release201520032005
Current release1.6.15, March 202211.1, February 2022
License infoCommercial or Open SourcecommercialOpen Source infoBSD licensecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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 languageCC++
Server operating systemsFreeBSD
Linux
OS X
Unix
Windows
Linux
Data schemeyesschema-freeyes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or datenoyes: 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.no
Secondary indexesnoNo Indexes Required
SQL infoSupport of SQLyes infothrough Apache DerbynoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Proprietary protocolADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
Java
Scala
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoRepcached, a Memcached patch, provides this functionallityMulti-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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyes infousing SASL (Simple Authentication and Security Layer) protocolfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
LeanXcaleMemcachedVertica infoVertica Analytics Platform
Specific characteristicsFull ACID and full SQL operational database with analytical queries over operational...
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Deploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
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Competitive advantagesLinear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
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Fast, scalable and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosHybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersbanking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metrics15 beta testers
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Licensing and pricing modelsannual fee covering license and support based on number of physical cores
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Cost-based models and subscription-based models are both available. One license is...
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LeanXcaleMemcachedVertica infoVertica Analytics Platform
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