DBMS > Machbase Neo vs. SpaceTime vs. SQream DB vs. Tarantool vs. Yaacomo

System Properties Comparison Machbase Neo vs. SpaceTime vs. SQream DB vs. Tarantool vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

TimeSeries DBMS for AIoT and BigData

SpaceTime is a spatio-temporal DBMS with a focus on performance.

a GPU-based, columnar RDBMS for big data analytics workloads

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Spatial DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	0.62
Rank	#234	Overall
	#109	Relational DBMS

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

Website

machbase.com

www.mireo.com/spacetime

sqream.com

www.tarantool.io

yaacomo.com

Technical documentation

machbase.com/dbms

docs.sqream.com

www.tarantool.io/en/doc

Developer

Machbase

Mireo

SQream Technologies

Q2WEB GmbH

Initial release

2013

2020

2017

2008

2009

Current release

V8.0, August 2023

2022.1.6, December 2022

2.10.0, May 2022

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

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

commercial

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++

C++, CUDA, Haskell, Java, Scala

C and C++

Server operating systems

Linux
macOS
Windows

Linux

BSD
Linux
macOS

Android
Linux
Windows

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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 query language

A subset of ANSI SQL is implemented

yes

Full-featured ANSI SQL support

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP API

.Net
JDBC
ODBC

Open binary protocol

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C#
C++
Python

C++
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions in Python

Lua, C and SQL stored procedures

Triggers

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Fixed-grid hypercubes

horizontal and vertical partitioning

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Real-time block device replication (DRBD)

none

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

Source-replica replication

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

volatile and lookup table

yes, full featured in-memory storage engine with persistence

yes

User concepts

Access control

simple password-based access control

yes

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

fine grained access rights according to SQL-standard

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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)

show all

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5 October 2023, fierce-network.com

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24 June 2020, SiliconANGLE News

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24 June 2020, VentureBeat

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25 June 2020, The Next Platform

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