DBMS > Amazon DynamoDB vs. Apache Impala vs. Geode vs. Hypertable vs. InfluxDB

System Properties Comparison Amazon DynamoDB vs. Apache Impala vs. Geode vs. Hypertable vs. InfluxDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Analytic DBMS for Hadoop

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

An open source BigTable implementation based on distributed file systems such as Hadoop

DBMS for storing time series, events and metrics

Primary database model

Document store
Key-value store

Secondary database models

Document store

Spatial DBMS

with GEO package

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Website

aws.amazon.com/dynamodb

impala.apache.org

geode.apache.org

www.influxdata.com/products/influxdb-overview

Technical documentation

docs.aws.amazon.com/dynamodb

impala.apache.org/impala-docs.html

geode.apache.org/docs

docs.influxdata.com/influxdb

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Hypertable Inc.

Initial release

2012

2013

2002

2009

2013

Current release

4.1.0, June 2022

1.1, February 2017

0.9.8.11, March 2016

2.7.6, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

GNU version 3. Commercial license available

Open Source

MIT-License; commercial enterprise version available

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

C++

Java

C++

Server operating systems

hosted

Linux

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X

through Homebrew

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (OQL)

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Java Client API
Memcached protocol
RESTful HTTP API

C++ API
Thrift

HTTP API
JSON over UDP

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC

.Net
All JVM based languages
C++
Groovy
Java
Scala

C++
Java
Perl
PHP
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication

selectable replication factor on file system level

selectable replication factor

in enterprise version only

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

yes, on a single node

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

Depending on used storage engine

User concepts

Access control

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights per client and object definable

simple rights management via user accounts

More information provided by the system vendor

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