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DBMS > Apache Impala vs. KairosDB vs. Tarantool vs. VictoriaMetrics

System Properties Comparison Apache Impala vs. KairosDB vs. Tarantool vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKairosDB  Xexclude from comparisonTarantool  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDistributed Time Series DBMS based on Cassandra or H2In-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSTime Series DBMSDocument store
Key-value store
Relational DBMS
Time Series DBMS
Secondary database modelsDocument storeSpatial 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
Score0.67
Rank#233  Overall
#20  Time Series DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteimpala.apache.orggithub.com/­kairosdb/­kairosdbwww.tarantool.iovictoriametrics.com
Technical documentationimpala.apache.org/­impala-docs.htmlkairosdb.github.iowww.tarantool.io/­en/­docdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaVKVictoriaMetrics
Initial release2013201320082018
Current release4.1.0, June 20221.2.2, November 20182.10.0, May 2022v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC and C++Go
Server operating systemsLinuxLinux
OS X
Windows
BSD
Linux
macOS
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesstring, 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.nononono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoFull-featured ANSI SQL supportno
APIs and other access methodsJDBC
ODBC
Graphite protocol
HTTP REST
Telnet API
Open binary protocolGraphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesAll languages supporting JDBC/ODBCJava
JavaScript infoNode.js
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-reducenoLua, C and SQL stored proceduresno
Triggersnonoyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding, 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 factorselectable replication factor infobased on CassandraAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Synchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Casual 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
Eventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberossimple password-based access controlAccess 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 ImpalaKairosDBTarantoolVictoriaMetrics
DB-Engines blog posts

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

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