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DBMS > Apache Impala vs. Google Cloud Bigtable vs. Sadas Engine vs. SpaceTime vs. TDSQL for MySQL

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. Sadas Engine vs. SpaceTime vs. TDSQL for MySQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpaceTime  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpaceTime is a spatio-temporal DBMS with a focus on performance.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.
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSSpatial DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtablewww.sadasengine.comwww.mireo.com/­spacetimewww.tencentcloud.com/­products/­dcdb
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationwww.tencentcloud.com/­document/­product/­1042
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleSADAS s.r.l.MireoTencent
Initial release20132015200620202013
Current release4.1.0, June 20228.0
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree trial version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++
Server operating systemsLinuxhostedAIX
Linux
Windows
Linuxhosted
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonononono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesA subset of ANSI SQL is implementedyes
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Python
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenononoyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningFixed-grid hypercubesAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnoneReal-time block device replication (DRBD)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infomanaged by 'Learn by Usage'nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardyesUsers with fine-grained authorization concept

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More resources
Apache ImpalaGoogle Cloud BigtableSadas EngineSpaceTimeTDSQL for MySQL
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