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DBMS > Apache Impala vs. Interbase vs. Kingbase vs. Tarantool

System Properties Comparison Apache Impala vs. Interbase vs. Kingbase vs. Tarantool

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonInterbase  Xexclude from comparisonKingbase  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopLight-weight proven RDBMS infooriginally from BorlandAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.In-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score0.50
Rank#257  Overall
#119  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteimpala.apache.orgwww.embarcadero.com/­products/­interbasewww.kingbase.com.cnwww.tarantool.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.embarcadero.com/­products/­interbasewww.tarantool.io/­en/­doc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEmbarcaderoBeiJing KINGBASE Information technologies inc.VK
Initial release2013198419992008
Current release4.1.0, June 2022InterBase 2020, December 2019V8.0, August 20212.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC and JavaC and C++
Server operating systemsLinuxAndroid
iOS
Linux
OS X
Windows
Linux
Windows
BSD
Linux
macOS
Data schemeyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.nono infoexport as XML data possibleyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesStandard with numerous extensionsFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
Open binary protocol
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoInterbase procedure and trigger languageuser defined functionsLua, C and SQL stored procedures
Triggersnoyesyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning (by range, list and hash) and vertical partitioningSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInterbase Change ViewsyesAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
Apache ImpalaInterbaseKingbaseTarantool
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Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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