DBMS > StarRocks vs. Tarantool vs. Warp 10 vs. Yanza

System Properties Comparison StarRocks vs. Tarantool vs. Warp 10 vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.starrocks.io

www.tarantool.io

www.warp10.io

yanza.com

Technical documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

www.tarantool.io/en/doc

www.warp10.io/content/02_Getting_started

Developer

The Linux Foundation

since Feb 2023

SenX

Yanza

Initial release

2020

2008

2015

Current release

2.5.3, March 2023

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

Open Source

Apache License 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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++

Java

Server operating systems

Linux

BSD
Linux
macOS

Linux
OS X
Windows

Windows

Data scheme

yes

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

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

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC
MySQL protocol

Open binary protocol

HTTP API
Jupyter
WebSocket

HTTP API

Supported programming languages

Java

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

Lua, C and SQL stored procedures

yes

WarpScript

Triggers

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

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range and hash)

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

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

based on HBase

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

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

yes

User concepts

Access control

Role based access control and fine grained access rights

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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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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