DBMS > Amazon DocumentDB vs. SAP HANA vs. TerarkDB vs. Tigris

System Properties Comparison Amazon DocumentDB vs. SAP HANA vs. TerarkDB vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

In-memory, column based data store. Available as appliance or cloud service

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store

Relational DBMS

Key-value store

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

aws.amazon.com/documentdb

www.sap.com/products/hana.html

github.com/bytedance/terarkdb

www.tigrisdata.com

Technical documentation

aws.amazon.com/documentdb/resources

help.sap.com/hana

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

www.tigrisdata.com/docs

Developer

SAP

ByteDance, originally Terark

Tigris Data, Inc.

Initial release

2019

2010

2016

2022

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

restricted open source version available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

Appliance or cloud-service

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

C++ API
Java API

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C++
Java

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using FoundationDB

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

yes

Access rights for users and roles

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