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DBMS > CrateDB vs. Drizzle vs. Hawkular Metrics vs. HBase vs. Vertica

System Properties Comparison CrateDB vs. Drizzle vs. Hawkular Metrics vs. HBase vs. Vertica

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionDistributed Database based on LuceneMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Wide-column store based on Apache Hadoop and on concepts of BigTableCloud 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 modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSTime Series DBMSWide column storeRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitecratedb.comwww.hawkular.orghbase.apache.orgwww.vertica.com
Technical documentationcratedb.com/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmlvertica.com/­documentation
DeveloperCrateDrizzle project, originally started by Brian AkerCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132008201420082005
Current release7.2.4, September 20122.3.4, January 202112.0.3, January 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoApache version 2commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono 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.
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 languageJavaC++JavaJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free, schema definition possibleYes, 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 dateyesyesyesoptions to bring your own types, AVROyes
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 indexesyesyesnonoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyes infowith proprietary extensionsnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBCHTTP RESTJava API
RESTful HTTP API
Thrift
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.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
C
C++
Java
PHP
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions (Javascript)nonoyes infoCoprocessors in Javayes, PostgreSQL PL/pgSQL, with minor differences
Triggersnono infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Multi-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 methodsnononoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
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 strategyACIDnoSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlrights management via user accountsPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
CrateDBDrizzleHawkular MetricsHBaseVertica infoOpenText™ Vertica™
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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CrateDBDrizzleHawkular MetricsHBaseVertica infoOpenText™ Vertica™
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