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

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

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Distributed Time Series DBMS based on Cassandra or H2

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store

Spatial DBMS

with Tarantool/GIS extension

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.60
Rank	#238	Overall
	#20	Time Series DBMS

Score	1.63
Rank	#139	Overall
	#25	Document stores
	#24	Key-value stores
	#65	Relational DBMS

Score	0.39
Rank	#269	Overall
	#43	Document stores
	#126	Relational DBMS

Website

impala.apache.org

github.com/kairosdb/kairosdb

www.tarantool.io

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

impala.apache.org/impala-docs.html

kairosdb.github.io

www.tarantool.io/en/doc

ydb.tech/en/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Yandex

Initial release

2013

2008

2019

Current release

4.1.0, June 2022

1.2.2, November 2018

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C and C++

Server operating systems

Linux

Linux
OS X
Windows

BSD
Linux
macOS

Linux

Data scheme

yes

schema-free

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Full-featured ANSI SQL support

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

Open binary protocol

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

All languages supporting JDBC/ODBC

Java
JavaScript

Node.js
PHP
Python

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Lua, C and SQL stored procedures

Triggers

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

simple password-based access control

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

Access rights defined for Yandex Cloud users

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More resources

DB-Engines blog posts

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

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