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DBMS > Datomic vs. Kingbase vs. RocksDB vs. Vertica

System Properties Comparison Datomic vs. Kingbase vs. RocksDB vs. Vertica

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonKingbase  Xexclude from comparisonRocksDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Embeddable persistent key-value store optimized for fast storage (flash and RAM)Cloud 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 modelRelational DBMSRelational DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score0.44
Rank#258  Overall
#117  Relational DBMS
Score2.84
Rank#97  Overall
#16  Key-value stores
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitewww.datomic.comwww.kingbase.com.cnrocksdb.orgwww.vertica.com
Technical documentationdocs.datomic.comgithub.com/­facebook/­rocksdb/­wikivertica.com/­documentation
DeveloperCognitectBeiJing KINGBASE Information technologies inc.Facebook, Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012199920132005
Current release1.0.7180, July 2024V8.0, August 20219.4.0, June 202412.0.3, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoBSDcommercial 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

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Implementation languageJava, ClojureC and JavaC++C++
Server operating systemsAll OS with a Java VMLinux
Windows
LinuxLinux
Data schemeyesyesschema-freeYes, 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 dateyesyesnoyes
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.noyesnono
Secondary indexesyesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoStandard with numerous extensionsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
C++ API
Java API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C++
Go
Java
Perl
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsuser defined functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peershorizontal partitioning (by range, list and hash) and vertical partitioninghorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesyesMulti-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 systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
DatomicKingbaseRocksDBVertica infoOpenText™ Vertica™
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