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DBMS > CrateDB vs. HBase vs. LMDB vs. Microsoft Azure Table Storage

System Properties Comparison CrateDB vs. HBase vs. LMDB vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHBase  Xexclude from comparisonLMDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionDistributed Database based on LuceneWide-column store based on Apache Hadoop and on concepts of BigTableA high performant, light-weight, embedded key-value database libraryA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Wide column storeKey-value storeWide column store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score2.09
Rank#121  Overall
#20  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitecratedb.comhbase.apache.orgwww.symas.com/­symas-embedded-database-lmdbazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcratedb.com/­docshbase.apache.org/­book.htmlwww.lmdb.tech/­doc
DeveloperCrateApache Software Foundation infoApache top-level project, originally developed by PowersetSymasMicrosoft
Initial release2013200820112012
Current release2.3.4, January 20210.9.32, January 2024
License infoCommercial or Open SourceOpen SourceOpen Source infoApache version 2Open Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Unix
Windows infousing Cygwin
Linux
Unix
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleschema-freeschema-free
Typing infopredefined data types such as float or dateyesoptions 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 indexesyesnonono
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynonono
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
RESTful HTTP API
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#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)yes infoCoprocessors in Javanono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
noneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
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 strategySingle row ACID (across millions of columns)ACIDoptimistic locking
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.noyesyesno
User concepts infoAccess controlrights management via user accountsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoAccess rights based on private key authentication or shared access signatures

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More resources
CrateDBHBaseLMDBMicrosoft Azure Table Storage
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