DBMS > Apache Impala vs. Apache IoTDB vs. Microsoft SQL Server vs. TDSQL for MySQL vs. Titan

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Microsoft SQL Server vs. TDSQL for MySQL vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

Analytic DBMS for Hadoop

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Microsofts flagship relational DBMS

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

impala.apache.org

iotdb.apache.org

www.microsoft.com/en-us/sql-server

www.tencentcloud.com/products/dcdb

github.com/thinkaurelius/titan

Technical documentation

impala.apache.org/impala-docs.html

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

learn.microsoft.com/en-US/sql/sql-server

www.tencentcloud.com/document/product/1042

github.com/thinkaurelius/titan/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Microsoft

Tencent

Aurelius, owned by DataStax

Initial release

2013

2018

1989

2013

2012

Current release

4.1.0, June 2022

1.1.0, April 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java

C++

Java

Server operating systems

Linux

All OS with a Java VM (>= 1.8)

Linux
Windows

hosted

Linux
OS X
Unix
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

JDBC
Native API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
Python
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C#
C++
Java
PHP
Python
Ruby

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

tables can be distributed across several files (horizontal partitioning); sharding through federation

Automatic sharding

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Integration with Hadoop and Spark

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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, groups and roles

based on Apache Sentry and Kerberos

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

User authentification and security via Rexster Graph Server

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