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DBMS > Apache Impala vs. Datomic vs. Google Cloud Bigtable vs. Kingbase vs. SwayDB

System Properties Comparison Apache Impala vs. Datomic vs. Google Cloud Bigtable vs. Kingbase vs. SwayDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKingbase  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Relational DBMSKey-value store
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.45
Rank#262  Overall
#123  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websiteimpala.apache.orgwww.datomic.comcloud.google.com/­bigtablewww.kingbase.com.cnswaydb.simer.au
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comcloud.google.com/­bigtable/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectGoogleBeiJing KINGBASE Information technologies inc.Simer Plaha
Initial release20132012201519992018
Current release4.1.0, June 20221.0.6735, June 2023V8.0, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercialcommercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureC and JavaScala
Server operating systemsLinuxAll OS with a Java VMhostedLinux
Windows
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyesno
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.nononoyesno
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoStandard with numerous extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Java
Kotlin
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsnouser defined functionsno
TriggersnoBy using transaction functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardinghorizontal partitioning (by range, list and hash) and vertical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACIDAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes 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.noyes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
Apache ImpalaDatomicGoogle Cloud BigtableKingbaseSwayDB
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