Index
A
- ACID properties / ACID guarantees
- advanced packaging tool (APT) / Installation using apt-get
- Apache Software Foundation (ASF) / Introduction to Cassandra
- Append-only Files (AOF) / Tunable data durability
- applications, MongoDB
- user profiles / MongoDB documents
- product and catalog data / MongoDB documents
- metadata / MongoDB documents
- content / MongoDB documents
- Atomicity, Consistency, Integrity, and Durability (ACID) / Modeling relational data
- attributes, DynamoDB / Tables, items, and attributes
- attributes, MongoDB / MongoDB documents
- availability / Consistency versus availability
- availability zone / Node configuration
- AWS
- used, for setting up DynamoDB / Setting up using AWS
B
- BATCH statements
- incorrect use / Incorrect use of BATCH statements
- ByteOrderedPartitioner, using / Using Byte Ordered Partitioner
- load balancer, using / Using a load balancer in front of Cassandra nodes
- framework driver, using / Using a framework driver
- best practices, DynamoDB
- table best practices / Best practices
- item best practices / Best practices
- query and scan best practices / Best practices
- local secondary indexes best practices / Best practices
- binary large object (BLOB) / Storing binary large object data
- Byte Ordered Partitioner (BOP) / Using Byte Ordered Partitioner
C
- cache sharding / Cache sharding
- CAP theorem / ACID guarantees
- Cassandra
- about / Introduction to Cassandra, Introduction to InfluxDB
- using / What problems does Cassandra solve?, Using Cassandra
- key features / What are the key features of Cassandra?
- tunable consistency / Tunable consistency
- data center awareness / Data center awareness
- linear scalability / Linear scalability
- building, with JVM / Built on the JVM
- use cases / Appropriate use cases for Cassandra
- internals, overview / Overview of the internals
- data modeling / Data modeling in Cassandra
- partition keys / Partition keys
- clustering keys / Clustering keys
- implementing / Putting it all together
- optimal use cases / Optimal use cases
- hardware, selecting / Cassandra hardware selection, installation, and configuration
- RAM / RAM
- CPU / CPU
- disk / Disk
- operating system / Operating system
- network/firewall / Network/firewall
- installation, with apt-get / Installation using apt-get
- tarball, installing / Tarball installation
- JVM, installing / JVM installation
- running / Running Cassandra
- node, adding to cluster / Adding a new node to the cluster
- nodetool / Nodetool
- CQLSH / CQLSH
- Python, using / Python
- Java, using / Java
- used, for backing up / Taking a backup with Cassandra
- snapshot, restoring from / Restoring from a snapshot
- executing, on Linux / Run Cassandra on Linux
- 7000 port / Open ports 7199, 7000, 7001, and 9042
- 7001 port / Open ports 7199, 7000, 7001, and 9042
- 7199 port / Open ports 7199, 7000, 7001, and 9042
- 9042 port / Open ports 7199, 7000, 7001, and 9042
- security, enabling / Enable security
- solid state drives (SSDs), using / Use solid state drives (SSDs) if possible
- seed nodes per data canter, configuring / Configure only one or two seed nodes per data center
- weekly repairs, scheduling / Schedule weekly repairs
- compaction, avoiding / Do not force a major compaction
- mutation / Remember that every mutation is a write
- data model / The data model is key
- support contract, considering / Consider a support contract
- references / References
- Cassandra, anti-patterns
- about / Cassandra anti-patterns
- frequently-updated data / Frequently updated data
- frequently-deleted data / Frequently deleted data
- queues / Queues or queue-like data
- solutions, with query flexibility / Solutions requiring query flexibility
- solutions, with table scans / Solutions requiring full table scans
- BATCH statements, incorrect use / Incorrect use of BATCH statements
- Cassandra Query Language (CQL) / Solutions requiring full table scans
- Cassandra Query Language Shell (CQLSH) / CQLSH
- casual clustering / Clustering, Causal clustering
- clustering key / Data modeling in Cassandra
- collections, MongoDB / MongoDB collections
- comma-separated values (CSV) / CQLSH
- compaction / Overview of the internals
- components, HBase
- Concurrent Mark and Sweep (CMS) / Configuration
- conditional operator
- applying, on filter parameter / Applying conditional and logical operators on the filter parameter
- consistency models, NoSQL databases
- strong consistency / Consistency versus availability
- timeline consistency / Consistency versus availability
- eventual consistency / Consistency versus availability
- coprocessors, HBase
- observers / HBase coprocessors
- endpoints / HBase coprocessors
- CRUD operations, DynamoDB / Data models and CRUD operations in DynamoDB
- Cypher / Cypher
D
- database, MongoDB / The MongoDB database
- data models, InfluxDB / Data model and storage engine
- data models, MongoDB
- about / Data models in MongoDB
- references document data model / The references document data model
- embedded data model / The embedded data model
- data structure server / Introduction to Redis
- data types, DynamoDB
- scalar type / Data types
- document types / Data types
- set types / Data types
- data types, MongoDB
- null / MongoDB data types
- boolean / MongoDB data types
- number / MongoDB data types
- string / MongoDB data types
- date / MongoDB data types
- array / MongoDB data types
- Embedded document / MongoDB data types
- documents, MongoDB / MongoDB documents
- document types, DynamoDB
- list / Data types
- map / Data types
- domain-specific language (DSL) / Kapacitor
- downloadable DynamoDB
- versus DynamoDB web services / The difference between downloadable DynamoDB and DynamoDB web services
- DynamoDB
- versus SQL / The difference between SQL and DynamoDB
- advantages / The difference between SQL and DynamoDB
- disadvantages / The difference between SQL and DynamoDB
- setting up / Setting up DynamoDB
- setting up, locally / Setting up locally
- setting up, AWS used / Setting up using AWS
- data types / DynamoDB data types and terminology, Data types
- tables / Tables, items, and attributes
- attributes / Tables, items, and attributes
- items / Tables, items, and attributes
- primary key / Primary key
- secondary indexes / Secondary indexes
- stream feature / Streams
- queries / Queries
- scan operation / Scan
- CRUD operations / Data models and CRUD operations in DynamoDB
- limitations / Limitations of DynamoDB
- best practices / Best practices
- DynamoDB streams
- DynamoDB web services
- versus downloadable DynamoDB / The difference between downloadable DynamoDB and DynamoDB web services
E
- embedded data model / The embedded data model
- Enterprise Management Associates (EMA) / Network management
F
- features, Neo4j
- clustering / Clustering
- Neo4j Browser / Neo4j Browser
- cache sharding / Cache sharding
- help for beginners / Help for beginners
- fields
- filters, applying on / Applying filters on fields
- file system (FS) cache / How does Neo4j work?
- filter parameter
- conditional operator, applying on / Applying conditional and logical operators on the filter parameter
- logical operators, applying on / Applying conditional and logical operators on the filter parameter
- filters
- applying, on fields / Applying filters on fields
- First In First Out (FIFO) / Queues
G
- Garbage-First Garbage Collector (G1GC) / Node configuration
- Gossiper / Introduction to Cassandra
- graph database management systems (GDBMS) / Analytics
H
- Hadoop Distributed File System (HDFS) / HDFS
- hardware calculator feature, Neo4j, Inc.
- reference / Disk
- hardware selection, Neo4j
- random access memory (RAM) / Random access memory
- CPU / CPU
- disk / Disk
- operating system / Operating system
- network/firewall / Network/firewall
- HBase
- table / Architecture, Logical and physical data models
- namespace / Architecture, Logical and physical data models
- region / Architecture
- RegionServer / Architecture
- components / Components in the HBase stack
- Zookeeper, using / Zookeeper
- system trade-offs / System trade-offs
- logical data model / Logical and physical data models
- physical data model / Logical and physical data models
- high availability / HBase high availability
- replicated reads / Replicated reads
- in multiple regions / HBase in multiple regions
- coprocessors / HBase coprocessors
- versus SQL / SQL over HBase
- HBase architecture / Architecture
- HBase Client API / Interacting with HBase – the HBase Client API
- HBase clusters
- interacting with / Interacting with secure HBase clusters
- HBase compactions / HBase compactions
- HBase master / HBase master
- HBase read path / The HBase read path
- HBase RegionServers / HBase RegionServers
- HBase shell / Interacting with HBase – the HBase shell
- HBase write path
- about / The HBase write path
- design motivation / HBase writes – design motivation
- high-availability (HA) / How does Neo4j work?
- Hive / Introduction to InfluxDB
I
- Industrial Internet of Things (IIoT) / Introduction to InfluxDB
- InfluxDB
- about / Introduction to InfluxDB
- key concepts / Key concepts and terms of InfluxDB
- data model / Data model and storage engine
- storage engine / Data model and storage engine, Storage engine
- installing / Installing InfluxDB
- installation link / Installing InfluxDB
- configuring / Configuring InfluxDB
- production deployment considerations / Production deployment considerations
- query language / Query language
- query pagination / Query pagination
- query performance optimizations / Query performance optimizations
- interaction, via REST API / Interaction via Rest API
- with Java client / InfluxDB with Java client
- with Python client / InfluxDB with a Python client
- with Go client / InfluxDB with Go client
- clustering and HA / Clustering and HA
- Retention Policy (RP) / Retention policy
- monitoring / Monitoring
- InfluxDB API client / InfluxDB API client
- InfluxDB ecosystem
- about / InfluxDB ecosystem
- Telegraf / Telegraf
- Kapacitor / Kapacitor
- InfluxDB operations
- about / InfluxDB operations
- backup / Backups
- restore / Restore
- Integrated Developer Environment (IDE) / Java
- Internet of Things (IoT) / Introduction to InfluxDB
- items, DynamoDB / Tables, items, and attributes
J
- Java
- Neo4j, using with / Java
- Java Management Extensions (JMX) / Built on the JVM
- Java virtual machine (JVM) / Random access memory
- Jedis
- reference / Java
K
- Kapacitor / Kapacitor
- key concepts, InfluxDB
- measurement / Key concepts and terms of InfluxDB
- field set / Key concepts and terms of InfluxDB
- field key / Key concepts and terms of InfluxDB
- field value / Key concepts and terms of InfluxDB
- tags / Key concepts and terms of InfluxDB
- continuous query / Key concepts and terms of InfluxDB
- line protocol / Key concepts and terms of InfluxDB
- point / Key concepts and terms of InfluxDB
- Retention Policy (RP) / Key concepts and terms of InfluxDB
- series / Key concepts and terms of InfluxDB
- timestamps / Key concepts and terms of InfluxDB
- Time Structured Merge (TSM) tree / Key concepts and terms of InfluxDB
- Write Ahead Log (WAL) / Key concepts and terms of InfluxDB
L
- labels / What is Neo4j?
- Last In First Out (LIFO) / Queues
- LazyWebCypher loader
- reference / Cypher
- least-frequently-used (LFU) policy / How does Neo4j work?
- legacy indexes / Indexing everything
- Linux
- Cassandra, executing / Run Cassandra on Linux
- log-structured merge (LSM) database / In-place updates versus appends
- Log-Structured Merge-Tree (LSM Tree) / Storage engine
- logical operators
- applying, on filter parameter / Applying conditional and logical operators on the filter parameter
M
- MongoDB
- download link / Installing of MongoDB
- installing / Installing of MongoDB
- data types / MongoDB data types
- database / The MongoDB database
- collections / MongoDB collections
- documents / MongoDB documents
- versus SQL / MongoDB documents
- advantages, over RDBMS / MongoDB documents
- uses / MongoDB documents
- applications / MongoDB documents
- limitations / MongoDB documents
- data models / Data models in MongoDB
- replication / Replication in MongoDB
- large data, storing / Storing large data in MongoDB
- MongoDB CRUD operations
- create operation / The create operation
- read operation / The read operation
- update operation / The update operation
- delete operation / The delete operation
- MongoDB indexing
- about / Introduction to MongoDB indexing
- default _id index / The default _id index
- single field / The default _id index
- compound index / The default _id index
- multikey index / The default _id index
- text indexes / The default _id index
- hashed index / The default _id index
- unique indexes / The default _id index
- partial indexes / The default _id index
- sparse index / The default _id index
- TTL index / The default _id index
- limitations / The default _id index
N
- namespace, HBase / Architecture, Logical and physical data models
- Neo4j
- about / What is Neo4j?
- working / How does Neo4j work?
- features / Features of Neo4j
- use cases / Evaluating your use case
- anti-patterns / Neo4j anti-patterns
- relational modeling techniques, applying / Applying relational modeling techniques in Neo4j
- using, for first time / Using Neo4j for the first time on something mission-critical
- entities, storing within entities / Storing entities and relationships within entities
- relationships, storing within entities / Storing entities and relationships within entities
- improper usage, of relationship types / Improper use of relationship types
- binary large object data, storing / Storing binary large object data
- indexes types / Indexing everything
- hardware selection / Neo4j hardware selection, installation, and configuration
- installing / Installation
- JVM, installing / Installing JVM
- configuration / Configuration
- high-availability clustering / High-availability clustering
- casual clustering / Causal clustering
- using / Using Neo4j
- using, with Python / Python
- using, with Java / Java
- backup, taking / Taking a backup with Neo4j
- restore, performing / Backup/restore with Neo4j Enterprise
- tips, for success / Tips for success
- references / Tips for success, References
- Neo4j Browser
- about / Neo4j Browser
- running / Neo4j Browser
- Neo4j Community
- backup, performing / Backup/restore with Neo4j Community
- restore, performing / Backup/restore with Neo4j Community
- versus Neo4j Enterprise / Backup/restore with Neo4j Community
- Neo4j Enterprise
- backup, performing / Backup/restore with Neo4j Enterprise
- network attached storage (NAS) / Disk
- network partition tolerance / What problems does Cassandra solve?
- node
- about / What is Neo4j?, Introduction to Cassandra
- configuring / Node configuration
- node/relationship cache / How does Neo4j work?
- nodetool / Using Cassandra
- NoSQL databases
- consistency models / Consistency versus availability
- hash, versus range partition / Hash versus range partition
- update, versus append / In-place updates versus appends
- storage models, comparing / Row versus column versus column-family storage models
- strongly, versus loosely enforced schemas / Strongly versus loosely enforced schemas
O
P
- partition key / Data modeling in Cassandra
- primary key, DynamoDB
- about / Primary key
- partition key / Primary key
- composite primary key / Primary key
- production deployment considerations, InfluxDB
- high availability / Production deployment considerations
- backups / Production deployment considerations
- security / Production deployment considerations
- proof-of-concept (POC) / Tips for success
- property graph model / What is Neo4j?
- Python
Q
- queries, DynamoDB / Queries
- query language, InfluxDB / Query language
- query pagination, InfluxDB / Query pagination
- query performance optimizations, InfluxDB / Query performance optimizations
R
- random access memory (RAM) / Random access memory
- Redis, anti-patterns
- about / Redis anti-patterns
- dataset / Dataset cannot fit into RAM
- relational data, modeling / Modeling relational data
- improper connection management / Improper connection management
- security / Security
- KEYS command, using / Using the KEYS command
- network time, reducing / Unnecessary trips over the network
- redundant array of independent disks (RAID) / Disk
- references document data model / The references document data model
- region, HBase / Architecture
- RegionServer, HBase / Architecture
- relational database management systems (RDBMS) / Analytics
- relational databases
- ACID properties / ACID guarantees
- relational modeling techniques
- applying, in Neo4j / Applying relational modeling techniques in Neo4j
- REmote DIctionary Server (Redis)
- about / Introduction to Redis
- key features / What are the key features of Redis?
- performance / Performance
- tunable data durability / Tunable data durability
- publish/subscribe / Publish/Subscribe
- data types / Useful data types
- data, expiring over time / Expiring data over time
- counters / Counters, Counters
- server-side Lua scripting / Server-side Lua scripting
- use cases / Appropriate use cases for Redis
- data / Data fits into RAM
- data durability / Data durability is not a concern
- data, scaling / Data at scale
- data model / Simple data model
- use case / Features of Redis matching part of your use case
- used, for data modeling / Data modeling and application design with Redis
- used, for application design / Data modeling and application design with Redis
- data structures, advantages / Taking advantage of Redis' data structures
- queues / Queues
- sets / Sets
- notifications / Notifications
- caching / Caching
- setting up / Redis setup, installation, and configuration
- installation / Redis setup, installation, and configuration, Installation
- configuration / Redis setup, installation, and configuration
- virtualization, versus on-the-metal / Virtualization versus on-the-metal
- RAM / RAM
- CPU / CPU
- disk / Disk
- operating system / Operating system
- network/firewall / Network/firewall
- configuration files / Configuration files
- using / Using Redis
- redis-cli / redis-cli
- Lua / Lua
- Python / Python
- Java / Java
- used, for obtaining backup / Taking a backup with Redis
- restoring, from backup / Restoring from a backup
- repair / Overview of the internals
- replicated reads, HBase / Replicated reads
- replication / Replication
- replication, MongoDB
- about / Replication in MongoDB
- automatic failover / Automatic failover in replication
- read operations / Read operations
- replication factor (RF) / CQLSH
- Retention Policy (RP) / Retention policy
- ring / Introduction to Cassandra
S
- scalar types, DynamoDB
- string / Data types
- number / Data types
- Boolean / Data types
- binary / Data types
- null / Data types
- scaling up / What problems does Cassandra solve?
- scan operation, DynamoDB / Scan
- schema indexes / Indexing everything
- secondary indexes, DynamoDB
- global secondary index / Secondary indexes
- local secondary index / Secondary indexes
- set types, DynamoDB / Data types
- sharding
- about / Sharding
- components / Sharded clusters
- advantages / Advantages of sharding
- Sorted String Table (SSTable) / Storage engine
- SQL
- versus MongoDB / MongoDB documents
- versus HBase / SQL over HBase
- versus DynamoDB / The difference between SQL and DynamoDB
- storage engine, InfluxDB / Data model and storage engine, Storage engine
- stream feature, DynamoDB / Streams
T
- tables, DynamoDB / Tables, items, and attributes
- tables, HBase / Architecture, Logical and physical data models
- Telegraf
- about / Telegraf
- data management / Telegraf data management
- time-series data
- use case / Introduction to InfluxDB
- Time Structured Merge Tree (TSM Tree) / Storage engine
- time to live / Expiring data over time
- tombstones / Overview of the internals
- top-level / Introduction to Cassandra
- transparent huge pages (THP) / Not disabling THP
U
- Ubuntu, in VirtualBox
- reference / Installing InfluxDB
- universally unique identifiers (UUIDs) / Data model and storage engine
- Usage Data Collector (UDC) / Configuration
- use cases, Neo4j
- social networks / Social networks
- matchmaking / Matchmaking
- network management / Network management
- analytics / Analytics
- recommendation engines / Recommendation engines
V
- virtualization
- versus on-the-metal / Virtualization versus on-the-metal
W
- write ahead log (WAL) / Storage engine, Configuring InfluxDB
Z
- Zookeeper
- features / Zookeeper