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DBMS > Apache Impala vs. EsgynDB vs. Google Cloud Bigtable vs. Immudb vs. Netezza

System Properties Comparison Apache Impala vs. EsgynDB vs. Google Cloud Bigtable vs. Immudb vs. Netezza

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonImmudb  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Data warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Key-value storeRelational DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.24
Rank#305  Overall
#43  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websiteimpala.apache.orgwww.esgyn.cncloud.google.com/­bigtablegithub.com/­codenotary/­immudb
immudb.io
www.ibm.com/­products/­netezza
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsdocs.immudb.io
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynGoogleCodenotaryIBM
Initial release20132015201520202000
Current release4.1.0, June 20221.2.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaGo
Server operating systemsLinuxLinuxhostedBSD
Linux
macOS
Solaris
Windows
z/OS
Linux infoincluded in appliance
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nononono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoSQL-like syntaxyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC protocol
PostgreSQL wire protocol
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Proceduresnonoyes
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACIDACID
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.nononono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept

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More resources
Apache ImpalaEsgynDBGoogle Cloud BigtableImmudbNetezza infoAlso called PureData System for Analytics by IBM
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