DBMS > Amazon Redshift vs. GeoMesa vs. Hazelcast vs. Tarantool vs. Warp 10

System Properties Comparison Amazon Redshift vs. GeoMesa vs. Hazelcast vs. Tarantool vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A widely adopted in-memory data grid

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

Primary database model

Relational DBMS

Spatial DBMS

Key-value store

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

with Tarantool/GIS extension

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

www.geomesa.org/documentation/stable/user/index.html

hazelcast.org/imdg/docs

www.tarantool.io/en/doc

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

CCRi and others

Hazelcast

SenX

Initial release

2012

2014

2008

2015

Current release

5.0.0, May 2024

5.3.6, November 2023

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

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

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Scala

Java

C and C++

Java

Server operating systems

hosted

All OS with a Java VM

BSD
Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

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.

yes

the object must implement a serialization strategy

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

Open binary protocol

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Event Listeners, Executor Services

Lua, C and SQL stored procedures

yes

WarpScript

Triggers

yes

Events

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

yes

Replicated Map

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

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

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

depending on storage layer

yes

yes, full featured in-memory storage engine with persistence

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

Role-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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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