DBMS > Amazon SimpleDB vs. Axibase vs. Hazelcast vs. TimescaleDB

System Properties Comparison Amazon SimpleDB vs. Axibase vs. Hazelcast vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

A widely adopted in-memory data grid

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Relational DBMS

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

Score	2.53
Rank	#111	Overall
	#21	Key-value stores

Score	0.30
Rank	#258	Overall
	#20	Time Series DBMS

Score	8.77
Rank	#48	Overall
	#5	Key-value stores

Score	2.93
Rank	#102	Overall
	#6	Time Series DBMS

Website

aws.amazon.com/simpledb

axibase.com/products/axibase-time-series-database

hazelcast.com

www.timescale.com

Technical documentation

docs.aws.amazon.com/simpledb

github.com/axibase/atsd

hazelcast.org/imdg/docs

docs.timescale.com

Developer

Amazon

Axibase Corporation

Hazelcast

Timescale

Initial release

2007

2013

2008

2017

Current release

15585

4.1.1, December 2020

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 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

Java

Server operating systems

hosted

Linux

All OS with a Java VM

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

Secondary indexes

yes

All columns are indexed automatically

yes

SQL

Support of SQL

SQL-like query language

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Go
Java
PHP
Python
R
Ruby

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Replicated Map

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Hazelcast is an in-memory computing platform that runs applications with extremely...
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Timescale is the creator of TimescaleDB , the first open-source relational database...
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Competitive advantages

Hazelcast has an optimized, multi-threaded architecture that enables the highest...
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TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
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Typical application scenarios

Hazelcast powers many types of large-scale, data processing applications. A sample...
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DevOps and Infrastructure Monitoring All monitoring data is time-series data. Efficiently...
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Key customers

Hazelcast customers include 50 of the world’s largest financial services companies,...
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TransferWise, Maersk, AppDynamics, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco,...
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Market metrics

With over 9,000 GitHub stars and growing, 600,000 active databases, and an active...
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Licensing and pricing models

Hazelcast provides both open source and commercial software. The open source offering...
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TimescaleDB comes in 3 versions, including fully managed Cloud-hosted solutions*,...
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