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DBMS > CrateDB vs. Postgres-XL vs. Sadas Engine vs. Vertica

System Properties Comparison CrateDB vs. Postgres-XL vs. Sadas Engine vs. Vertica

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSadas Engine  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionDistributed Date Store based on LuceneBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSADAS 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 modelRelational DBMS
Search engine
Relational DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Time Series DBMS
Document store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#178  Overall
#86  Relational DBMS
#13  Search engines
Score0.70
Rank#206  Overall
#97  Relational DBMS
Score0.00
Rank#354  Overall
#152  Relational DBMS
Score19.29
Rank#38  Overall
#24  Relational DBMS
Websitecrate.iowww.postgres-xl.orgwww.sadasengine.comwww.vertica.com
Technical documentationcrate.io/­docswww.postgres-xl.org/­documentationwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbvertica.com/­documentation
DeveloperCrateSADAS s.r.l.Micro Focus infoprior to that Hewlett Packard
Initial release20132014 infosince 2012, originally named StormDB20062005
Current release10 R1, October 20188.011.1, February 2022
License infoCommercial or Open SourceOpen SourceOpen Source infoMozilla public licensecommercial 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 languageJavaCC++C++
Server operating systemsAll OS with a Java 7 (and higher) VMLinux
macOS
AIX
Linux
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyesyesyes: 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.noyes infoXML type, but no XML query functionalitynono
Secondary indexesyesyesyesNo Indexes Required
SQL infoSupport of SQLyes, but no triggers and constraintsyes infodistributed, parallel query executionyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET infocommunity maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesErlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
Ruby infocommunity maintained client
Scala infocommunity maintained client
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioninghorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-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 systemEventual Consistency
Read Your Own Writes Consistency infofor primary key lookups
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
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 strategyACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standardAccess 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
CrateDBPostgres-XLSadas EngineVertica infoVertica Analytics Platform
Specific characteristicsCrateDB is an open source distributed SQL database that spreads data and processing...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more
Competitive advantagesCrateDB is typically used in operational analytics applications, particularly those...
» more
Fast, scalable and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersCrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsThe CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
» more
Licensing and pricing modelsCrateDB pricing CrateDB Community Edition is open source and free to use under the...
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
CrateDBPostgres-XLSadas EngineVertica infoVertica Analytics Platform
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