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DBMS > Apache Impala vs. HBase vs. Tkrzw vs. TypeDB vs. WakandaDB

System Properties Comparison Apache Impala vs. HBase vs. Tkrzw vs. TypeDB vs. WakandaDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHBase  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopWide-column store based on Apache Hadoop and on concepts of BigTableA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query languageWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSWide column storeKey-value storeGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Object oriented DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Score0.65
Rank#234  Overall
#20  Graph DBMS
#107  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteimpala.apache.orghbase.apache.orgdbmx.net/­tkrzwtypedb.comwakanda.github.io
Technical documentationimpala.apache.org/­impala-docs.htmlhbase.apache.org/­book.htmltypedb.com/­docswakanda.github.io/­doc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoApache top-level project, originally developed by PowersetMikio HirabayashiVaticleWakanda SAS
Initial release20132008202020162012
Current release4.1.0, June 20222.3.4, January 20210.9.3, August 20202.26.3, January 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache version 2Open Source infoApache Version 2.0Open Source infoGPL Version 3, commercial licenses availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++JavaC++, JavaScript
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
Linux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-free, schema definition possibleschema-freeyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROnoyesyes
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.nonononono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnononono
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
Thrift
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
Python
Ruby
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoCoprocessors in Javanonoyes
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoby using Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
noneMulti-source replication infoby using Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoyes infoby using Apache Kafka and Apache Zookeeperno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)ACIDACID
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.noyesyes infousing specific database classesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoyes infoat REST API level; other APIs in progressyes
More information provided by the system vendor
Apache ImpalaHBaseTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetTypeDB infoformerly named GraknWakandaDB
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
Apache ImpalaHBaseTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetTypeDB infoformerly named GraknWakandaDB
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